Nacho Palou

With their effort and knowledge, Telefónica Tech's #LadyHacker demonstrate that progress has no gender. * * * Who are you and what do you do for a living? I'm Tamires Abujamra, an occasional player of board games (laughs). I am also Nico's mum, my dog and lifelong friend. I am a publicist by training, but since the beginning of my career I have worked in product, with technology. I am currently responsible for the Cross team of Telefónica Tech IoT in Brazil, and I am in charge of Mobility, Retail and Energy Efficiency products. How would you describe your career so far and what are the skills you use at Telefónica Tech? My professional career started in a telecommunications company in 2008 and to this day I still work in technology, where dynamism and change are constant elements. The skills I use the most are creativity, especially to face challenges in the best possible way and the search for innovation. The power of thinking about solutions in different ways combined with the search for the fresh can open up new paths and make the journey easier. What do you consider to be the specific challenges women face in the IT sector and how have you overcome these challenges throughout your career? There are many challenges, from matching salaries to proving that we are competent professionals. I have always been very clear about my professional goal and I always try to trust in my talent and potential, but in the end it is inevitable to put ourselves in check. I have had exceptional leaders throughout my career who have been important and empowering pillars in this process, in addition to the entire structure of Telefónica Tech Brazil, which has been doing a very solid job in this area over the years, generating empowerment and valuing diversity. Tamires Abujamra, Telefónica Tech Brasil. What makes Telefónica Tech a great place to work for women and how does the company promote gender diversity and inclusion? There are targets for women in leadership positions and the incentive to hire as diverse a team as possible. Diversity goes hand in hand with social equality and consequently generates a much wider repertoire. There are more and more women in leadership positions and this scenario is growing, we are encouraged to seek our positions and we are valued. What kind of initiatives or schemes do you think are needed to encourage women's participation and success in the technology field? The first step is to accept that there is no gender-related differentiation in capacity or level of knowledge. What really determines an individual's potential and capacity is his or her background, commitment, information, and experience. The second step is that women must seek to occupy their place, and the company and employees in general must act as facilitating agents for this. Information and re-education are essential elements in this transformation. It is a cultural process that requires transparency on all sides and communication is the key to this change. There is no gender-related differentiation in capacity or level of knowledge. Tamires Abujamra & Nico, Telefónica Tech Brasil. What does Lady Hacker initiative mean to you? It is another essential step to value and break paradigms, to give voice to women, to those who from their position have the opportunity to share ideas and experiences. #LadyHacker is the kind of action we need to engage and bridge the gap between genders and other paradigms. How do you think your experience and perspective as a woman have influenced your approach and technology projects? My experience helped me to be perseverant and to always look for new solutions, even working in something new like the innovation area of Teléfonica Tech Brazil. Telefónica Tech Meet #LadyHacker Karla Parra, Cybersecurity expert at Telefónica Tech June 20, 2023 Telefónica Tech Meet #LadyHacker Jess Woods, Cloud expert at Telefónica Tech March 8, 2023

July 28, 2023, marked a milestone in telecommunications. Sateliot, a pioneer in operating a constellation of 5G IoT satellites, Telefónica Tech, and Telefónica Global Solutions, successfully established a 5G roaming connection from space for the first time. This enabled global NB-IoT connectivity. The test, supervised by the European Space Agency (ESA), successfully demonstrated the satellite extension of our NB-IoT connectivity using the GSMA roaming standard. As it's a standard protocol (3GPP), IoT devices seamlessly and securely connect to both terrestrial and non-terrestrial networks. The architecture designed to enable this connection integrates Sateliot's satellite network with Kite's network nodes, Telefónica Tech's IoT connectivity platform. In the test, we used a standard SIM card installed on an IoT device. The SIM card, managed through our Telefónica Tech Kite platform, successfully and seamlessly connected to Sateliot's network. This validated the authentication of a conventional roaming connection through their LEO satellite network, in Low Earth orbit. Convergence between Terrestrial and Non-Terrestrial Mobile Networks This test utilized 'Store & Forward' technology and a two-step authentication method adapted to enable a conventional roaming connection between a terrestrial mobile network and a non-terrestrial LEO (Low Earth Orbit) network. LEO satellites orbit in low Earth orbit, typically at altitudes of 500 to 600 kilometers. Thanks to 'Store & Forward' technology, Sateliot's 5G network stores data collected from IoT devices while satellites are out of position to connect to a ground station. It then transmits the data when they enter the coverage area. Our collaboration with Sateliot not only represents a significant advancement in global NB-IoT connectivity. Also holds significant potential for the IoT device industry. 'Store & Forward' technology and the ability for IoT devices to transmit data through a roaming interface using the two-step authentication method will pave the way for commercial deployment in 2024. AI of Things 5 free online courses to learn IoT (Internet of Things) in 2023 August 3, 2023 Global IoT connectivity applications and benefits The results obtained offer numerous opportunities to enhance the quality of life for millions of people worldwide. This is especially true for those living in areas without terrestrial networks access. It also offers the potential to increase operational efficiency for businesses, foster innovation, and improve how we interact with our environment. Some examples include livestock and agriculture monitoring, efficient management of natural resources like water or energy, applications in land or maritime logistics operations, infrastructure maintenance, combating poaching, preserving natural spaces and the environment, or detecting and responding to emergencies anywhere on the planet, among others. NB-IoT satellite connectivity enables maritime and on-the-move IoT coverage. Image: Yaroslav Danylchenko / Freepik. Starting in 2024, Telefónica will become the first operator to provide global NB-IoT connectivity through hybrid IoT connectivity, combining terrestrial and satellite NB-IoT networks. This connectivity can work with conventional and affordable IoT devices. Towards a more connected and efficient world Global IoT connectivity has become essential for a growing range of sectors, from agriculture to logistics to renewable energies. Our collaboration with Sateliot represents a significant step forward in creating a global communication network capable of addressing upcoming challenges and needs. Thanks to the convergence between terrestrial and non-terrestrial networks, we can offer NB-IoT connectivity in remote locations without terrestrial network coverage, as well as backup coverage in areas with existing wireless coverage, and maritime coverage for IoT use cases on the move. This further expands the potential applications of IoT technology to to build a more connected, sustainable, and efficient future. AI of Things The potential of Artificial Intelligence of Things to transform a wide range of Industries July 26, 2023

Unlearning in Artificial Intelligence (AI), or 'machine-unlearning,' is the process of updating or modifying the acquired knowledge of an AI model based on the latest information or changes in the scope of application or circumstances. It can also be motivated by technical considerations or regulatory requirements, for example. Unlearning refers to adjusting or eliminating existing data, rules, or connections in an AI model. It is an "emergent subfield of machine learning that aims to remove the influence of a specific subset of training examples from a trained model, ideally while preserving intact valid data and learning," as explained by Google. Machine unlearning tackles challenges such as data bias and adaptation to changing scenarios or regulations. Why machine-unlearning matters in AI Machine unlearning is fundamental because AI models often encounter changing, biased, contradictory, or excessive data. Maintaining previous connections acquired from such data can lead to incorrect or biased decisions. As explained in SemiWiki, "adaptability is a cornerstone of intelligence, both human and artificial. Just as humans learn to navigate new situations and respond to changing environments, AI systems strive to exhibit a similar capacity.” It is added that one of the advantages of adaptability through machine unlearning is the mitigation of a phenomenon known as 'catastrophic forgetting.' When AI models are trained with updated data inconsistent with the original training data, there is a risk of "forgetting" (overwriting or losing) valuable training. Proper and controlled unlearning helps address catastrophic forgetting by carefully eliminating obsolete or incorrect information while preserving previously acquired knowledge. Therefore, machine-unlearning enables AI models to be more flexible and adaptable. It also allows them to make more precise and fair decisions as they are used because unlearning enables: Correcting Biases and Errors Biases and errors in training data can lead to biased or ineffective AI models. Machine unlearning allows the identification and correction of these biases by eliminating or modifying connections that lead to unfair or incorrect decisions. Example: A personnel selection model with acquired gender or age biases can correct them through unlearning. Adapting to changes AI models, like humans, must adapt to new data, regulations, or circumstances. Machine unlearning enables models to update their knowledge as they encounter updated or changing information. Example: A news recommendation system can adjust user preferences as their interests change. Improve accuracy and generalization Machine unlearning can enhance models' generalization ability by removing obsolete or noisy information that could negatively affect their performance. Example: A machine translation model that has learned incorrect grammar rules can unlearn those rules to produce accurate translations. Benefits of machine unlearning Machine unlearning has been used to enhance AI models' accuracy and fairness in various applications, such as personnel selection, fraud detection, or medical diagnosis. Benefits of machine unlearning in AI include: Improving performance by reducing outdated data and models that slow down the system. Protecting sensitive information or individual privacy. Making AI systems more efficient in processing new information. Enhancing AI's ability to process and analyze complex data. Correcting biases acquired during training. Enabling more precise predictions and recommendations tailored to changes in user habits and preferences. AI of Things Ghosts in the machine: does Artificial Intelligence suffer from hallucinations? February 20, 2023 Challenges in AI unlearning Machine unlearning in AI faces significant challenges. Some experts even doubt its effectiveness: "To use a human analogy, once an A.I. has ‘seen’ something, there is no easy way to tell the model to ‘forget’ what it saw. And deleting the model entirely is also surprisingly difficult", says Fortune. Google also points out that "fully erasing the influence of the data requested to be deleted is challenging since, aside from simply deleting it from databases where it’s stored, it also requires erasing the influence of that data on other artifacts such as trained machine learning models". In the face of this difficulty, Google launched the first Machine Unlearning Challenge this summer. Machine unlearning faces challenges, just like other approaches such as retraining or regularization, including: Obtaining suitable, quality, and relevant datasets can be challenging, especially if data is scarce or difficult to collect. Modifying AI models' complex internal representations can be challenging, as is identifying which parts of the model need to be modified and how to do it properly. Improper or unbalanced application can lead to unwanted results, such as removing useful information (overfitting) or not removing enough biased information (underfitting). Understanding changes and consequences well to avoid opacity and ensure accountability, including for AI decisions before unlearning. Implementing techniques to measure accuracy, fairness, and other relevant aspects of the updated model and ensuring effective improvements. Even resetting an AI model to completely erase previous knowledge and enable new learning from scratch is a complex process. Training or retraining an AI model can be very expensive depending on its size and complexity. "GPT-4 was probably trained using trillions of words of text and thousands of computer processors in a process that cost more than 100 million euros," according to Wired. Conclusion Machine unlearning plays a fundamental role in improving AI models' accuracy, fairness, privacy, and adaptability. It enables models to update and modify their previous knowledge based on new information or changes in the environment. Therefore, as AI influences more aspects of our lives, machine unlearning becomes an essential tool to ensure AI models are fair, accurate, and adaptable. However, finding a balance between effective learning and unlearning in AI is still a major challenge. AI of Things What is AI-winter and how to avoid it June 6, 2023 Image: Freepik.

Actualizado: 21/08/2023 The European Drought Observatory (EDO) monitors, analyses, forecasts and measures the impact of droughts and their consequences on the economy, agriculture and other areas. In its latest report of June 2023, EDO highlights the "serious drought" that hurts "broad areas of Europe" amid "warmer than average" summers and less rainfall, especially north and center. EDO recommends "close monitoring" of the evolution of the drought and adopting adequate water use plans in order to anticipate and mitigate its effects on water resources: The summer of 2023 currently has a high risk of being critical with respect to water resources According to the latest map of the Combined Drought Indicator 14% of the EU territory is in Warning conditions and 10% is in Alert conditions. Image: European Union / EDO Technology for the digital transformation of water resources Water is a natural resource that is as valuable as it is scarce and requires smart management of its integral cycle through the digital transformation of water management companies. Telefónica Tech's Smart Water solution applies technology to give water management companies greater control of water use, distribution and recovery in order to: Improve supply management to minimise leakage and adapt infrastructure investment plans. Guarantee the correct recovery, treatment and use of the used water. Raise awareness and empower consumers by giving them greater control and information on what their water consumption is and how to reduce it. All this is possible thanks to the intelligent sensorisation of water distribution networks. Telefónica Tech works with specialised partners such as Contazara and Idrica to implement IoT and data analytics technologies with Big Data and Artificial Intelligence aimed at the integrated management of the water cycle. In this way, management companies have much more metrological information and in-depth knowledge of what is happening in their network, from monitoring water quality at different points in the network to receiving detailed data on the volumes distributed or variations in flow rates. Advantages of more efficient water management For instance, detecting anomalies with respect to average measurements or differences between volumes distributed and volumes consumed makes it possible to identify fraudulent consumption, leaks or water losses at the time they occur, both in the network and at the household level. Digitalisation of the complete water cycle saves millions of m3 of water each year and reduces operation and maintenance costs by 20% and maintenance costs by 20%, according to Idrica. Data from the sensorisation of water infrastructures also allows water managers to improve their processes —such as prioritising interventions according to the criticality of the detected incident— and to make an accurate prediction of demand to meet consumption. Making strategic decisions based on data even makes it possible to accurately anticipate seasonal or one-off demands, such as the influx of tourists or the holding of large events, for example. This leads to more efficient water management and savings in operating and energy costs. At the same time, the environment is protected and an adequate supply of water in terms of both quantity and quality is guaranteed. How Smart Water's solution helps Canal de Isabel II improve its water distribution service Canal de Isabel II (CYII) manages more than a dozen reservoirs in six river basins to supply water to more than 6 million people. CYII is using Telefónica Tech AI of Things products and services to address its digital transformation, with the objectives of: optimise its sourcing processes and operations, provide a better service to its customers, protect this resource from inefficient consumption. In this case, as part of the Smart Water solution, Telefónica Tech, together with Contazara, is working on the deployment of smart meters that allow remote reading of water meters. Thanks to these connected IoT meters, the company receives a reading of consumption every hour or according to the customer's needs, instead of working with estimated consumption or with readings taken by hand every two months. Benefits of the Smart Water solution for consumers This amount of data provides Canal de Isabel II with greater knowledge of what is happening in its network, and of the consumption habits of its customers. For the consumer, this has benefits such as, for instance: know their consumption and compare it between periods and with the average consumption of households with a similar profile. pay for actual consumption and not estimates, which reduces complaints and billing incidents. receive personalised savings plans and recommendations to reduce water consumption, and therefore the amount of the bill. detect anomalous consumption (by default or excess), for example in second homes or in the homes of dependent persons. Remote reading of water meters has an additional environmental benefit by reducing fuel consumption and pollutant emissions from travelling to check, maintain and read meters. Technology is key to efficient and sustainable water management However, remote meter reading is only one part of Telefónica Tech's Smart Water solution that allows water managers to undertake a complete digital transformation of the entire water cycle. This allows them to address the smart management of a resource that is so sensitive to climate change, weather variations and increased demand. Today more than ever, it is not only the health and well-being of consumers that depend on the proper and sustainable management of the complete water cycle - from its collection, treatment and distribution to its recovery, purification and reuse or return to watercourses. The economy and sectors such as industry, livestock, agriculture, tourism... and, of course, the environment, also depend on it. AI OF THINGS AI of Things (II): Water, a sea of data March 16, 2022

Internet of Things (IoT) is one of the new generation digital technologies with significant impact in multiple sectors, from industry to agriculture, health, and energy. IoT creates new business opportunities and is changing the way companies, industries, administrations, and also people, interact with the world. An IoT device is one that has the ability to capture or generate data (for example, a temperature sensor) and has internet connectivity to transfer that information. In this way, IoT allows capturing, processing, and exchanging information efficiently and effectively. Among other applications, IoT allows monitoring and optimizing from traffic to resources such as energy, water, or people's health, and is enabling the development of smart cities, autonomous vehicles, precision agriculture, or smart industry, among many other possibilities. Today, knowing the principles of IoT technology is essential for both students and professionals in the technology sector. But how to get started in IoT technology? Where to begin? In this post, we compile a selection of free and online courses that you can follow at your own pace to learn about this technology. Knowing IoT technology not only opens up new professional opportunities, but also allows understanding how technology works and how it influences people's lives and the environment. Introduction to the Internet of Things IoT (Curtin University): This free course (with the option to acquire a certification) explores the IoT concept and physical devices ('things') that make the Internet of Things possible, including how components communicate with each other, how to extract value from the data they generate, and some considerations related to IoT Cybersecurity and privacy. Requires 1.5 months dedicating 2-3 hours per week. Introduction to the Internet of Things and Embedded Systems: This 11-hour course, offered by the University of California and available on Coursera, is part of a specialized program 'An Introduction to Programming the Internet of Things (IoT)', which consists of a total of 6 courses with level advances. This first course explains the role of IoT, what are the most common devices, and trends for the future. It also deals with topics related to the components, both software and hardware of the devices, and their interface with the physical world. Finally, the key components of interconnection are explained. Introduction to IoT (Cisco Networking Academy): This free course (optional certification) of 20 hours addresses how digital transformation is creating economic opportunities and how IoT is changing the way companies operate and manage their processes and systems, without forgetting the Cybersecurity considerations that must be addressed when implementing IoT solutions. AWS IoT: Developing and Deploying an Internet of Things: Free (optional certification). 4 weeks. This Amazon (AWS) course covers general content such as "What is the Internet of Things and how does it work?" to more specific content about AWS services. To take this course, it is recommended to have at least one year of software development experience and basic knowledge of AWS services and console. Introduction to Azure IoT: This course is the first module of the Microsoft Certified AI Edge engineer. The first course in the program provides an introduction to the different services that can be condivd in Azure to design large-scale IoT solutions. All modules and courses are available for free on Microsoft Learn, excluding the certification. AI OF THINGS How to start programming in Artificial Intelligence: languages, tools and recommendations January 18, 2023 Conclusion It's worth noting that, except for some cases, most of these courses are introductory. However, they provide knowledge of this technology and its components and practical applications. In addition, they cover topics such as network architecture, sensors, embedded systems, communication protocols, security and privacy measures, data analysis tools, cloud platforms, and an overview of Artificial Intelligence algorithms. One advantage is that they are free (except for certification, which is usually optional and requires a fee) and open to anyone interested. They are also self-paced, allowing them to be completed at one's own pace. The use of IoT will continue to grow in the coming years with the adoption of an increasing number of IoT devices in all types of sectors and industries, homes and businesses, and cities. Overall, these types of courses are an excellent way to acquire new skills and knowledge in a short amount of time, in just a few days or weeks. These courses also serve as a complement to other related technologies, such as Cloud and Edge Computing, 5G and NB-IoT connectivity, Big Data and data analysis, Artificial Intelligence and machine learning models, industrial automation technologies, smart city infrastructures, etc. Any of these courses is an excellent option to take the first steps in IoT.

Digitalisation has led to the creation of smart spaces where the physical and the digital converge. These smart spaces can be public places with different purposes: from shops and shopping centres to hotels or football stadiums. In any case, the aim of smart spaces is to be more efficient and sustainable, and to offer the public a more interactive and personalised experience in order to adapt to a hyper-connected customer whose demands and preferences are constantly changing. Smart retail: physical and digital merging in retailing In this sense, one of the main trends is the smart retail, the digitalisation of physical retail spaces incorporating digital technologies. This is achieved with the sensorisation of the physical environment thanks to IoT (Internet of Things) and the incorporation of connectivity, smart and interactive screens, virtual and augmented reality... It is possible to offer customers a better shopping experience when they visit physical spaces by applying data analytics and Artificial Intelligence to the data captured by sensors. Companies and brands must take advantage of digital technologies to strengthen their business, generate new shopping experiences and be more competitive. Interactive, immersive, and efficient phygital shops The interactivity enabled by phygital shops provides users with real-time information, personalised offers and recommendations, and a high level of investment that enhances the experience, reduces lost sales opportunities, and increases loyalty. For example, augmented reality allows users to view products, access detailed descriptions and even 'try on' items virtually. This translates into more responsive consumers, longer dwell time in physical and online shops and increased conversion rates. Image: gpointstudio / Freepik Dynamic marketing platforms also make it possible to tailor on-screen messages to the context and profile of the customer, who can incorporate data from e-commerce such as product ratings or purchase history. In this way, the experience becomes omnichannel and more personal. The omni-channel shopping experience The omni-channel shopping experience removes the barriers between the physical and digital environments to create a unified experience, flowing between the digital and physical channels used by the shopper by incorporating digital technologies into physical spaces. This makes it possible to offer: Personalised offers and interactions according to the user's profile. Option to buy online and pick up in shop or vice versa. Connection of physical stocks with e-commerce. Services such as smart lockers to speed up deliveries and returns. Unified experience between the online and offline world. Brands can deliver seamless experiences, satisfy consumers who no longer distinguish between physical and digital channels, and increase conversion rates. AI of Things You can already maximise the impact of your campaigns in the physical space April 26, 2022 Internal improvements and process optimisation in smart retail Beyond improving the customer experience, digitalisation also optimises internal business processes. Technologies such as RFID and smart shelves or smart labels allow, for example, to: Real-time tracking of inventory and stock levels to identify consumption trends and enhance stock management. Utilize product traceability to optimize product logistics and supply chain. Optimize human resources allocation based on foot traffic and sales data. Brands gain profitability, reduce operating expenses and boost customer satisfaction by implementing technology solutions in inventory management and logistics. The power of data in phygital shops In the data economy, having the ability to identify consumer preferences and behaviours provides a competitive advantage for retail spaces by enabling, among other advantages, Quantify the traffic of potential customers and their conversion rates. Understand the paths within the shop and the interest shown in a product. Dynamically personalise content according to the shopper's offline and online profile. Identify which sections or areas of the shop generate more (or less) interest among visitors. Optimise opening hours and staffing based on context and occupancy data. This enables brands to make decisions that help them optimise their strategies, spaces, and resources to achieve more sales and reduce costs while responding to users' interests and providing a better shopping experience. AI of Things Socio-demographic segmentation and video analytics to improve shopping experience July 13, 2022

In an increasingly digitized world, acquiring basic Cybersecurity knowledge is crucial to protect ourselves from growing cyber threats. We all need to understand how to identify risks, adopt secure practices, and safeguard our privacy. This applies not only in professional settings but also in personal situations. For example, charging our phones outside, using online banking, or scanning a restaurant menu with a QR code. A foundational Cybersecurity course allows us to learn the best practices for protecting our personal and financial information. Therefore, basic Cybersecurity knowledge is indispensable for anyone using technology. As our lives become more digitalized, cyber threats increase. Introduction to Cybersecurity Course, free and in Spanish In this regard, Cisco Networking Academy offers a wide range of courses related to Cybersecurity, designed to provide the necessary technical knowledge and skills in various areas such as cloud security, network security, and endpoint security. One of these courses is Cisco's Introduction to Cybersecurity, available for free on the Skills for All platform. This caters to individuals at any prior knowledge. This self-paced course, offered in multiple languages, requires approximately 6 hours of dedication and can be completed at your own pace. To access and complete the course, all we need is a computer or mobile device and an internet connection. The introductory course consists of 5 modules and 7 practical exams. It equips us with the knowledge required to protect our digital lives, understand security risks and how to mitigate them, as well as ethical and legal aspects. Through this course, we can strengthen our communications, devices, and privacy security. The Introduction to Cybersecurity course is just the beginning of a series of courses that form the Cybersecurity Learning Pathway. This learning path includes simulations and practical exams at different levels and topics, preparing you for the Certiport Information Technology (IT) Specialist Cybersecurity certification, specifically targeted at those starting out in Cyber Security. Cyber Security How language puts business Cybersecurity at risk June 1, 2023 The Key to Cybersecurity: Education + Awareness Any Cyber Security strategy includes awareness and education as fundamental tactics to strengthen digital security. However, it's imperative to note the difference between "awareness" and "education" in the field of Cybersecurity. Awareness aims to educate and cultivate a security mindset. Education focuses on technical knowledge and skills. This combination is essential to have the right mindset but also the knowledge that protects us against cyber threats. While awareness stems from education and knowledge, "awareness alone can induce fear, paralysis, or indifference," wrote our Cybersecurity expert Sergio de los Santos recently. __ Cisco is part of the Telefónica Tech partner ecosystem, the network of alliances that allows us to develop the most advanced solutions on the market for our clients. Image from Freepik.

Artificial Intelligence has the potential to transform the way we interact with technology, as well as redefining the boundaries of what is possible. AI has demonstrated its ability to generate cross-cutting benefits in many areas, from improving human wellbeing and health to driving environmental sustainability. Its application in the operations of organisations, companies and industrial sectors enables new business models. It also changes the way we research and innovate, improves the efficiency and sustainability of production processes and supply chains, and redefines our capabilities and ways of working. However, along with the opportunities it offers, with AI also come ethical challenges and responsibilities that must be proactively addressed to responsibly harness the potential and benefits offered by Artificial Intelligence. The European Parliament says Artificial Intelligence can boost European productivity by 11-37% by 2035 In this sense, the responsibility by design approach applied to Artificial Intelligence is a strategy that ensures that AI systems and models are developed and used from their conception in an ethical, transparent, and accountable way. What is the 'responsibility by design' approach to AI? The principle of responsibility by design is a methodology that is applied in different sectors and industries, from scientific research to urban planning to the design of common products and services. In the field of Artificial Intelligence, responsibility by design refers to the integration of ethical and responsible considerations from the early stages of design to anticipate and address potential ethical, legal and social issues that may arise with the use of AI. This implies that AI designers and developers must take into account aspects such as transparency, fairness, privacy, security and social impact, both of the models and algorithms as well as the data used, in order to build a trustworthy Artificial Intelligence. Accountability by design is not only applied from the beginning of the process, but also throughout the entire development lifecycle to assess possible impacts and consequences in different evolutions, scenarios, cultures, and contexts. AI of Things Ghosts in the machine: does Artificial Intelligence suffer from hallucinations? February 20, 2023 AI responsible by design An accountability by design approach based on existing methodologies (e.g., privacy and security) raises some considerations to be taken into account from the initial conceptualisation and development phases, and throughout the entire model cycle, to ensure ethical and responsible development of AI projects, including: Having multidisciplinary and diverse teams (including experts in ethics, legislators, industry, civil society...) to incorporate different perspectives and knowledge, avoiding bias and discrimination in the results. Self-assess throughout its development and operation the possible undesirable effects it may have on users, society and the environment. Define security measures in the handling of information and personal data to ensure user privacy and regulatory compliance. Understanding at all times and throughout the development, learning and deployment process how it works and how it makes decisions, allows to understand and explain why it makes decisions and helps to detect biases. Constantly monitor throughout its lifecycle how it works to identify potential impacts as it evolves and is applied in different domains and contexts. Our Artificial Intelligence principles In this regard, at Telefónica Tech we adopt the ethical principles for AI that Telefónica Group defined in 2018. They form part of a broader methodology focused on responsibility by design and commit us to develop and use Artificial Intelligence that is: Fair, so that the models do not generate results with discriminatory or unfair biases or impacts. Transparent and explainable, disclosing the data we use to train the models and their purpose, ensuring that their decisions are understood. People-centred, respectful of Human Rights and aligned with the UN Sustainable Development Goals. Respectful by design of the privacy of people and their data, and information security. Truthful in its logic and in the data used, including by our suppliers. We further require our suppliers to have similar AI principles or to adopt our own, with the aim of building, together, AI models that harness the potential and benefits offered by AI while protecting human rights, democracies and the rule of law. AI of Things Can Artificial Intelligence understand emotions? May 23, 2023 Featured image: This is Engineering RAEng / Unsplash.

Before shutting down your computer and heading out for vacation, there's one detail you shouldn't forget: setting up an "out of office" (OoO) message is a common practice to inform your clients and colleagues that you'll be away for a few days. However, when configuring an OoO message, it's crucial to find a balance between providing useful information, individual privacy, and company security. Additionally, since the automatic response is typically sent without distinguishing the sender, whenever your email client allows it —such as in Outlook— you may consider setting up two different messages: a more detailed one for trusted colleagues and clients, and a generic one to respond to any other sender. What to include (and not) in an OoO message For a generic message, it's important to limit personal information since the same text will be returned as a response to any incoming message: whether it's for a trusted contact or a malicious actor. As much as possible: Avoid including unnecessary personal details such as exact dates, destination, specific activities, or individuals you'll be with. Not even a mobile for contact. You only have to inform that you are going to be away for a few days. Refrain from revealing sensitive company information like "If you're writing regarding Project X, contact...". If you mention an alternative contact, ensure it's someone who is aware of your absence, ongoing tasks, authorized, and genuinely able to assist the sender during your absence. Of course, confirm with that person first before including them as an alternative contact. Cloud Cloud Computing still running on holidays August 23, 2023 How to configure an effective and secure OoO message When writing an out-of-office message in your corporate email account, the text should be concise. Since you don't know who will write during your absence and what the reason is, avoid informal or creative language. At least not too much. Also remember that the person writing to you is probably not on vacation. A secure out-of-office message could be: Hello, Thank you for your message. I am currently out of the office but will reply to your email upon my return. Best, If you feel it's necessary to provide a reference to help the sender manage their expectations regarding a response, you can add a non-specific timeframe, such as: ...I will respond to your email in the second half of August. Not providing an exact return date, besides being more secure, gives you a margin of time upon your return. This way, you can review the emails received during your absence calmly and prevent the same emails from arriving again from a specific day onwards. Upon your return, you can dedicate more time and attention to messages received during your absence. This is always beneficial to avoid rushing when responding, and mistakes such as downloading an attachment, or clicking on any suspicious link. Photo by Ethan Robertson / Unsplash.

According to a survey conducted by Business Insider, 43% of workers use Artificial Intelligence tools like ChatGPT or Bing to assist them in their professional tasks, as these tools provide information and function as advanced search engines. However, as we increasingly rely on these tools, experts emphasize the need to protect our privacy and the sensitive information of companies. In this regard, it is imperative to note that while an Artificial Intelligence model provides answers, it also generally uses the question and information contained in the query to learn and improve its responsiveness. Although, in general, the obtained information is used in an aggregated and anonymous manner (without identifying the provider), it should be noted that it can be used later to better understand and respond to new queries, including those made by other users. Data you should not share with ChatGPT (and similar models) Therefore, with Artificial Intelligence models like ChatGPT, you should not share any information that can be considered personal, private, secret, or confidential. For example, Data that can identify a specific person, reveal personal information, or facilitate identity theft: full name, date of birth, postal address, ID number, phone number, email address... Confidential data, highly specific programming code from your development, information about undisclosed products, or trade secrets of your company, to prevent them from being exposed due to data leaks or unauthorized access to your model's account, and to avoid their appearance in future responses to other users. Banking data or information that, if leaked, could be used for fraud, identity theft, or social engineering attacks. Additionally, it is not advisable to share medical data, such as test results or diagnoses, and any other health-related information that could be recorded in your conversation history and linked to your user account in the AI model's app or website. Some measures for safer queries When sharing information with Artificial Intelligence models like ChatGPT, it is advisable to take certain measures to protect your privacy, data, and sensitive or confidential information: Include in your query only public and limited information, avoiding personal data that identifies an individual. If necessary, use fictional or generic information and avoid providing details that could link you to other people, companies, or places. While it is a growing trend, it is generally not a wise idea to share overly specific information about your vacation dates and detailed travel itinerary. For free Artificial Intelligence models like ChatGPT, consider having two accounts, one anonymous and not associated with your identity. When in doubt, it is always safer to use your mobile data connection instead of an open or public Wi-Fi network, such as those in cafés or hotels. Do not share login credentials and refrain from asking ChatGPT to generate a password that meets the specific length and character requirements of a particular service. Avoid sharing medical data, banking information, or any other information that is or should be protected. It is also important to familiarize yourself with the terms of use and privacy policies of Artificial Intelligence models (they are quite good at summarizing them, so take advantage of it) to understand how your account data and the information you provide to the model are used, and if they are shared (how and for what purpose) with third parties, such as other companies. ⚠ Some AI services warn about the possibility of 'human review' of queries, for quality reasons or because it is an experimental product, and ask not to enter personal data or confidential information. Artificial Intelligence models like ChatGPT can be extremely useful for a wide range of tasks. These tasks range from preparing Hollandaise sauce to drafting an email in another language. However, it is imperative to acknowledge that they come with the same security and privacy risks associated with other platforms, such as social media. Therefore, it is equally important to take measures to make the most of their benefits in the safest possible manner. Cyber Security AI of Things Cyber Security Evolution: AI as a Tool for Attack and Defence June 28, 2023 Photo: frimufilms en Freepik.

A new Trending Techies event was held yesterday, a face-to-face meeting organised by Telefónica Tech to generate community and conversation between professionals, students, companies and the public interested in new generation digital technologies. The event, hosted by Manu de Luna, data scientist at Telefónica Tech, was attended by four professionals and experts who spoke and discussed with attendees about the responsible use of data in Artificial Intelligence models. AI systems transparency The first presentation was given by Cristina Contero, from Aphaia, with her talk "Mirror, mirror, what's behind this AI". Cristina spoke about the different categories of Artificial Intelligence and how all of them are already subject to regulation through, among other laws prior to any regulation that may apply, the General Data Protection Regulation (GDPR). In this sense, Artificial Intelligence (or 'automated decision-making processes', for the purposes of the GDPR) is intrinsically related to data. Whether the data used to train AI models includes personal information or whether automating decisions affects the fundamental rights of individuals. "If our AI uses personal data today, it already has to meet a number of transparency requirements," she explained. AI cannot be understood without widespread adoption. Therefore, it is the developers themselves who are looking for confidence in these systems. AI-guided digital workers In his presentation "Digital Workers guided by AI: a challenge with many benefits", Marty Mallavibarrena, Senior Solutions Consultant at SS&C Blue Prism, explained how RPA (Robotic Process Automation) platforms work. These platforms allow software (non-physical) robots to be created and put to work to perform repetitive tasks. This can include, for example, reading ID card data when someone sends it to register for a service, or when filing a claim with the insurance company. These RPA platforms are increasingly applying Artificial Intelligence techniques to make these "digital coworkers" more effective and efficient and meet market demands. In his presentation, Marty explained some use cases and thought-provoking examples, and discussed the ethical and technical challenges for the responsible application of AI in this area. Among them, how to control biases in data and models at source and data compliance. Keys to harnessing AI tools in journalism Teresa Mondría, product manager at Igeneris, shared a talk on how to use new technologies to innovate in journalism. In this case, the use of AI as a journalistic tool affects both those who produce information and the people who consume it. Teresa explained with specific examples the real applications of AI in the news production process, such as in translations, verification (debunking hoaxes, checking data...) or in the research and analysis of large volumes of documentation. "Tasks where AI brings a differential value and can be very useful." It is also applied to news tagging, social listening, or content recommendation. Teresa shared the keys for journalists to incorporate Artificial Intelligence in the production of information: Respond to a target Treat the AI as a source (and sources are verified). Understand how and by whom the data is processed Give assurances to journalists and readers Be transparent Unbiased data: preventing bias The challenge of impartiality in AI in investigative journalism and data' was the fourth and final presentation of the meeting. Delivered by Antonio Delgado, co-founder of Datadista. He highlighted how AI helps to process and analyse data, especially when it comes to large volumes of information. What used to be slow clustering processes are now tasks that are done in seconds thanks to AI. However, he highlighted the importance of data fairness when training and using AI models. When it comes to data journalism, tools like ChatGPT bring significant ethical and practical challenges around fairness." Language models such as GPT have been trained by extracting data from the internet and can therefore learn and reproduce biases in that data. On the contrary, "when using an AI model trained with our own data and information sources, they allow us to perform tasks such as searching and summarising information in large volumes of documents efficiently, analysing large datasets to discover patterns and trends, and prototyping content quickly." In this case, nevertheless, "we must be aware and critical of the potential biases that we ourselves can introduce into our training data, to ensure the impartiality and accuracy of our work." Antonio shared three keys to avoid introducing biases into our models: Algorithms must be transparent and understandable. Apply ethical codes of journalism Verify the facts and data obtained (AI as a source) If you would like to participate or attend the next Telefónica Tech Trending Techies join the Cyber Security Techies or Data Techies meetup communities.

Our series of interviews with #WomenHackers from Telefónica Tech continues. The purpose of this is to get to know a little better the experts who, with their knowledge and skills, make us more capable and innovative. * * * Who are you and what do you do? I am Karla Parra, systems engineer, runner, passionate about technology, cyber security, and digital transformation. I have more than 20 years of professional experience leading the management of operations, commercial, product development and pre-sales for cyber security services, IT services, IT and information security, technological continuity, and business continuity. I currently lead the Cybersecurity and Cloud Provisioning team at Telefónica Tech Hispam & USA. What is your specialisation and how did you come to do what you do now? The specialisation I have is aligned to Cybersecurity and management. However, my beginnings were not in technology. I studied forestry engineering, but life led me to the world of technology, drawing me to the analysis and research side, which is why I followed the line of cyber security. Was it clear to you at an early age that you wanted to work in the world of technology? Was it something vocational? When I was a child, it was not clear to me that I was going to dedicate myself to the world of technology. I dreamt of other professions, such as doctor, veterinarian, park ranger… The things that happen during our lives, and the fact that I am curious, allowed me to learn about an exciting career that few people were betting on. How would you describe your career so far and what are the skills you use at Telefónica Tech? Karla Parra, Head of Cyber Security & Cloud Provision Perú I would describe my professional career as challenging, passionate, and fun. I enjoy what I do, and I don’t stop learning every day, because technology is constantly evolving, especially in the field of security. The skills I use are respect, humility, and commitment. I believe these are essential skills in security, where professional ethics are your trademark and allow you to gain the trust of your customers, your team, and the company. It is crucial to achieve your goals. What do women bring to STEAM professions? Every individual brings something to the world of technology. In the case of women, I feel that we complement with our analytical approach and attention to detail. In the Cybersecurity sector we have female profiles, and we are seeing more and more participation. In fact, according to IT User, women occupied 10% in 2013, 20% in 2019 and 25% in 2022, these figures translate into an increase of women in Cyber Security of 150% in the last decade. The digital transformation is a valuable opportunity to balance the participation of women in the technological world. The digital transformation we are experiencing today is a valuable opportunity to balance the participation of women in the technological world due to greater flexibility, hybrid work or labour demand, among other factors. What makes Telefónica Tech a great place to work for women and how does the company promote gender diversity and inclusion? Telefónica Tech allows me to develop professionally and provides me with work facilities so that I can take on the different roles that we have to live as women. We currently have 30% female participation in the operational areas in Peru In this way, emphasis is placed on equal and fair participation between genders by promoting women’s participation. In this regard, we have recently held two events that have given us the opportunity to promote diversity and inclusion: Leading the Tech World, where I had the opportunity to share the conversation with two great professionals from the world of technology: Elena Gil – Global Director of Product Commercial Operations; and Carolina Navarrete – Director Marketing B2B HISPAM. The objective of the session was to transmit our experiences and challenges that we have as women in the technological world. HackaCyber, a hacking party full of challenges designed to discover the different strengths of the students, which allowed new talents to be identified. This experience speaks volumes about the importance of maintaining these spaces to discover and encourage the development of talent, and thus increase the presence and involvement of women in the technological world. Could you explain to us what the Lady Hacker initiative means to you? Karla Parra, part of the Telefónica Tech #LadyHacker initiative It means inspiring and motivating more and more women to show their talent in the world of technology and cyber security. It means contributing my professional experience to build a safer world. What advice would you give to other women who want to pursue a STEAM career? The advice I would give them is to be confident. To be challenging, self-learners and, above all, to enjoy what they do. In the ever-changing world of technology, our strategy must be to stay one step ahead. Telefónica Tech Meet #LadyHacker Jess Woods, Cloud expert at Telefónica Tech March 8, 2023 Telefónica Tech “To be a hacker in life is to be a passionate, talented person who manages to influence the transformation of society", Carmen Alonso July 28, 2022 Telefónica Tech «We are moving towards genderless professions», María Martínez August 8, 2022 Telefónica Tech #LadyHacker Tamires Abujamra is innovating at Telefónica Tech Brazil September 14, 2023

The Digital Enterprise Show 2023 (DES) has come to an end after one of the most exciting and intense weeks of the year. As we say goodbye to Málaga, we also say goodbye to our headquarters for the Telefónica Tech Laboratory and Innovation Area, making the capital of the Costa del Sol a benchmark in cyber security and technological innovation. This year’s DES event celebrates its seventh edition, becoming an international meeting of reference on trends and technologies enabling digitization and digital transformation of companies of all sizes and sectors. Telefónica Tech has been a global sponsor at DES 2023, sharing space, knowledge, products and conversations with tens of thousands of professionals from around the world, including experts, managers and professionals from multiple sectors, including banking, health, energy, tourism, commerce, mobility or industry. Welcome to our booth at DES 2023 The Telefónica Tech booth at DES 2023 At DES 2023, we provided attendees with a networking area and product exhibition. There were also five experiential areas dedicated to our IoT technologies, Big Data, Artificial Intelligence, Blockchain, Cybersecurity, Cloud, that attracted a good number of professionals. Telefónica Tech stand institutional visit Our stand also hosted representatives from different institutions, such as Francisco de la Torre, the mayor of Malaga, Juanma Moreno, the president of the Junta de Andaluca, and Francisco Salado, the president of the Malaga Provincial Council, on the opening day. They were accompanied by María Jesús Almazor, CEO of Telefónica Tech, and Joaquín Segovia, director of Telefónica’s southern territory. Attendees enjoyed the demos we presented and our value proposition during their visit, including: The ThinX Lab At DES 2023, our applied technology laboratory The ThinX will be featured on Telefónica Tech’s stand Bringing a little bit of The ThinX, our open lab for AI of Things. In our pioneer space The ThinX, clients, partners, and organizations can test their IoT projects in real conditions, reducing costs and speeding up development and deployment. Visitors to our lab were able to see connected V16 beacons, Geotab tracking devices for fleet management, smart lighting solutions, and components of our Smart Water solution, among others, that have passed through our laboratory. Digital Operations Center (DOC) An area of the Telefónica Tech booth at DES 2023 was dedicated to our Digital Operations Center (DOC). Our DOC (Digital Operations Center) provides comprehensive and global services for the monitoring and operation of our clients’ Cybersecurity and Cloud services. Physically located in Madrid, Spain, and Bogotá, Colombia, the DOC, in coordination with our SOC, brings together thousands of cybersecurity and cyberintelligence experts. Demo: Quality Control with Industrial IoT This small demo combines advanced technologies such as our private 5G networks, Edge Computing solutions, vision algorithms and Artificial Intelligence. It automates a real-time industrial monitoring and classification task. Audiovisual Portfolio In addition, customers could firsthand, accompanied by our experts and through audiovisual means, learn about our portfolio of solutions and capabilities. In addition, customers could learn about success stories. Telefónica Tech eShop Telefónica Tech's eShop corner Because well-being and leisure time are also of importance, our visitors, clients, and friends explored and acquired some of the products from our eShop. Our participation in talks and presentations At DES 2023, we took part in various talks and presentations where our Telefónica Tech experts shared their knowledge, experiences, and projects: ◾ Daniel Ribaya, Director of Cloud Products and Services, gave a talk titled ‘Discover Edge Computing With Telefónica Tech. In this talk, he discussed the role of Edge Computing technology and the benefits of bringing Cloud capabilities to where they are needed. This includes reducing response times (latency), and ensuring data security. Telefónica Tech in Spain is at the forefront of implementing both Proof of Concepts (PoCs) and real customer deployments of Edge Computing, 5G connectivity, and the Internet of Things (IoT). ◾ Juan Campillo, Director of Product Marketing for Cybersecurity, participated in the ‘Inspiration Theatre’ with his talk ‘Guardians of the Digital Frontier’. I would like to bring some optimism for those of us who find ourselves in the ‘valley of despair.’ A formula for cyber resilience in critical infrastructure is risk = probability x impact. ◾ Alexis Hostos took the stage with his speech on ‘The Silent Revolution: Technology and Innovation in Future SMEs.’ Besides highlighting the importance of innovation and digitization to ensure SMEs’ sustainability and continuity. The question we should ask ourselves is not ‘what future our SMEs can have,’ but ‘what future we want them to have.’ ◾ María Jesús Almazor, CEO of Cybersecurity and Cloud at Telefónica Tech, participated in the event ‘Meet the Disruptors: A Conversation with Game Changers and Visionaries.’ There is no single order of importance for technologies. Beyond ensuring basic technologies are implemented correctly and building more comprehensive solutions, the greatest power of digital transformation is achieved. ◾ Alfredo Serret, our Global Managing Director of Business Development, and Manu Marin from Livall participated in the talk ‘Accelerating Towards a New Ecosystem: Mobility, Cities, and Data.’ ◾ José Luis Núñez, our Blockchain Lead, was present at the event ‘The Web3 Super App that Connects City, Businesses, and People through the New European Digital Identity (EU ID Wallet)’ at the Smart Cities & Urban Mobility Forum. Blockchain is the online digital notary for information exchanged between individuals, businesses, and services that was not public or verifiable until now. During the second day of DES 2023, we continued to share our knowledge and experience in different presentations, talks, and panel discussions, including: ◾ Maria Muñoz Ferrer, Business Development Director, and José Luis Domínguez, Sales Director, spoke about digital services and the use of enabling technologies such as Big Data, Cybersecurity, Cloud, and Artificial Intelligence in the presentation ‘Towards a Happy Citizen’. The application of next-generation digital technologies creates a new paradigm that also responds to digital transformation needs and the new challenges faced by relevant sectors of public management: health, employment, and tourism. All of this is aimed at providing a better citizen experience and improving service management. ◾ Carlos Martínez Miguel, Global Director of IoT, Big Data, and Artificial Intelligence Solutions and Services, was present with his talk ‘Embracing the Power of Big Data and AI. In this talk, he discussed how organizations are leveraging business transformation opportunities enabled by Big Data and Artificial Intelligence. Artificial Intelligence brings significant opportunities but also significant challenges. All stakeholders must work together to manage them. ◾ Peter Moorhead, Head of Security Pre-Sales at Telefónica Tech UK&I, participated in the panel ‘Challenges, Issues and Opportunities of Managing Global Health Locally. Big Data and Privacy,’ where he shared insights regarding data privacy in healthcare. One of the main challenges is knowing where healthcare data is stored and how it is used, with the goal of guaranteeing patient privacy. We couldn’t miss our appointment with the audience on the last day of DES 2023 either: ◾ Andrés Escribano, Director of New Business and Industry 4.0, spoke in ‘Revolutionizing Industries: Exploring the Power of Industry 4.0, IoT, and Digital Technologies’ about the technologies that are transforming the industry towards a more efficient, productive, and sustainable model. We can measure the real impact digitization and associated technologies have on companies’ results and KPIs. ◾ Alberto Sempere, Director of Product and Innovation, participated in the CEO & Leadership Summit with his presentation ‘Zero Trust Everywhere, all at once. He highlighted that the current level of disruption is an overhaul for all companies and enables innovation for “differentiation paths.” Applying a Zero Trust mindset helps us increase our resilience and digital sovereignty. ◾ Esther Cardenal, Senior Product Manager, participated in the Retail & Logistics Forum, in the session ‘The Wellness Center of the Future. In this session, she discussed the implementation of our video analytics and Artificial Intelligence solution in GO fit centers. Manuel Estébanez, CEO of GO fit, talked about the challenge of implementing this technology to extract knowledge from data while respecting user privacy. Technology plays an essential role in sports and wellness center design.

As we discussed in a previous article, Edge AI and Cloud AI are two different approaches to implementing Artificial Intelligence developments or machine learning models. In a nutshell, Cloud AI stores and processes data on Cloud platforms or servers, where AI algorithms and models are executed. Edge AI captures or receives data and runs AI algorithms and models on local devices such as wearables, IoT devices, or Edge Computing servers. Since each approach has its advantages and disadvantages, the choice between the two models will depend on the project’s needs and requirements, context, environment, and even location. Edge AI advantages In Edge AI: Artificial Intelligence outside Cloud, we saw that even in environments with poor coverage or no connectivity, Edge AI can make decisions, execute instructions, or provide real-time insights or responses. This is especially crucial for critical IoT solutions in industries like manufacturing (IIoT), healthcare (IoMT), or mobility. This is made possible because Edge devices can capture, process, and analyze data locally, close to where the data is generated or needed. For example, in factories, offices, hospitals, or farms, without the need to send large amounts of information to remote servers or cloud platforms. It can even function without relying on a permanent broadband connection or low latency. Additionally, Edge AI offers additional advantages: By processing and storing data on the device, the risk of interception or storage by third parties is reduced. It also reduces exposure during transmission or storage. This often provides greater control over the data and makes it easier to comply with local regulations regarding data protection, residency, or privacy. Operational cost savings, as only the most relevant or already processed data is sent to the cloud. This typically requires less computing power and storage space in the cloud. Edge AI devices can be configured and programmed according to the project’s needs at a relatively low cost, allowing for customization and adaptation to the solution to make them more efficient. Edge AI disadvantages Edge AI devices have limited data processing and storage capacity. Some tactics, such as algorithm optimization or the use of Application-Specific Integrated Circuits (ASICs) applied to Artificial Intelligence, can improve their performance. However, their capacity is still limited compared to cloud platforms’ virtually unlimited resources. This characteristic can limit the complexity of machine learning models and Artificial Intelligence algorithms that can be executed on Edge AI devices. This is particularly relevant to devices like wearables or IoT sensors that operate on battery power. Algorithm execution consumes significant energy, diminishing autonomy. Additionally, it’s worthwhile to consider that: Incorporating Artificial Intelligence or machine learning capabilities into specifically designed devices can result in higher hardware costs than equivalent devices or IoT sensors without this capability. For the same reason, these devices often require more maintenance, both at the hardware and software levels, to ensure they remain updated and operational. Although storing and processing data locally has advantages, Edge AI devices are also vulnerable to security or privacy breaches and attacks, exposing their data to potential attackers. Encryption or obfuscation can help protect Edge AI data. Cloud AI advantages Scalability, capacity, and accessibility are some of the main attributes and advantages of the Cloud. Cloud AI is capable of processing and storing large amounts of data, even massive volumes, adapting to the needs and demands. Cloud AI also: Often, they utilize well-known platforms with abundant training and informational resources. This streamlines the deployment of Artificial Intelligence models through intuitive interfaces and training and deployment tools that simplify implementation. For this reason, implementing Cloud-based Artificial Intelligence solutions can be simpler and cheaper than implementing Edge AI solutions on proprietary hardware. The cloud allows companies to pay only for the resources they need (pay-as-you-go), saving costs on infrastructure, maintenance, and personnel. It is accessible from anywhere and at any time, as long as there is an internet connection. This enables remote and real-time access to processed data, facilitating integration with other existing applications and business processes. Additionally, automatic hardware and software updates provided by Cloud providers ensure that Cloud AI solutions run on up-to-date platforms with the latest security updates. Cloud AI disadvantages Availability and latency (the time it takes for data to be sent and received between the device and the cloud) can be problematic for applications that require real-time response. Data processing and machine learning consume high resources, increasing operational costs. Sending data and information to Cloud platforms can pose risks, regulatory non-compliance, and even data exposure, especially when dealing with sensitive data transferred to third-party Cloud platforms in cross-border regions. Cloud AI applications require a robust and capable internet connection. This can be a hurdle in environments or areas with limited connectivity, low bandwidth, or no connection or coverage. Differences in Security: Risks and Challenges As we have seen, both approaches entail risks and challenges regarding data security. Edge AI is worth noting for the following reasons: Edge devices, being located in accessible physical environments, may be more prone to physical attacks, including theft, breakage, or tampering. Edge devices are also vulnerable to interceptor attacks during data transmission or storage on the device. The diversity and quantity of Edge devices and proprietary developments can make security updates challenging, leaving them vulnerable to threats. Limitations of Edge devices can also hinder sophisticated security measures, like end-to-end encryption or biometric identification. Risks and security challenges in Cloud AI: Cloud service providers implement appropriate security measures to prevent data theft, leaks, or security breaches. In some cases, sensitive data may be subject to specific regulations regarding data location and residency. If cloud providers fail to comply with these regulations, they risk regulatory non-compliance. When using third-party cloud services, data protection policies and privacy regarding data protection depend on the Cloud provider. The time required to transmit data to and from the cloud (latency) can create delays, which can be problematic for applications requiring real-time responses. Additionally, lack of connectivity or interruptions can affect cloud services availability and access. When is Edge AI more suitable? When is Cloud AI better? The choice between Edge AI and Cloud AI depends on the specific use case. This will depend on factors such as connectivity availability, scalability, or data sensitivity. Edge AI is highly suitable for situations where real-time response is required or network connectivity is limited. For example, In industrial environments, Edge AI allows for real-time processing of sensor data without latency, ensuring no interference with the production process. In healthcare, Edge AI can process patient information without medical data leaving hospital premises. This provides an immediate response that is vital in critical situations. Self-driving robots, autonomous vehicles, drones, or AGVs (Automatic Guided Vehicles). On the other hand, Cloud AI is more suitable in situations where scalability is essential to handle large volumes of data. For example, In logistics or e-commerce companies, Cloud AI enables efficient processing and analysis of vast amounts of information, including user data, customer data, and transactions. Banking risk analysis and fraud detection require processing large amounts of data to identify complex patterns. This is done to detect suspicious or fraudulent operations. In services like automatic translation or voice recognition, Cloud AI can perform large-scale language analysis and understanding, improving response accuracy and quality. Some applications will require immediate response and less dependence on network connectivity, while others will require extensive processing and data analysis capabilities. Ethical considerations: a common need for both approaches Both Edge AI and Cloud AI require careful consideration of data security and privacy. In the case of Edge AI, it is imperative to ensure that data is adequately protected on Edge devices and that there are no risks of privacy breaches or unauthorized access. In the case of Cloud AI, it is necessary to verify that Cloud service providers have appropriate security policies and measures in place to protect data and comply with data protection regulations. In both cases, Artificial Intelligence development and models should avoid biases and discrimination. This can happen because the data used to train the models may be biased, or because the algorithms themselves unintentionally introduce biases. To mitigate biases and discrimination, it is necessary to conduct testing and evaluations that identify and address potential biases. This ensures that AI systems are fair and unbiased. Furthermore, Artificial Intelligence implementation, whether in Edge AI devices or Cloud AI, requires careful consideration of responsibility and accountability. It is critical to clearly define who is responsible for AI systems’ outcomes and functioning, and to establish mechanisms to address any issues or consequences that may arise. Lastly, it is always critical to understand and explain how AI models work, how they make decisions, and how they generate results. Therefore, ensuring transparency and explainability of the algorithms and AI models used is essential, particularly in critical domains such as healthcare. Artificial Intelligence ethical considerations should be comprehensively and carefully addressed throughout the entire development and implementation process. This is regardless of whether the model is applied using Edge AI or Cloud AI approach. The goal is to ensure that AI models are fair, transparent, explainable, responsible, and respectful of privacy and individual rights. More articles in this series: Raspberry Pi for Edge AI: Artificial Intelligence at the Edge for Everyone. Edge AI: Artificial Intelligence outside Cloud. Featured photo: DilokaStudio on Freepik.

Google Cloud has recently launched some new free courses focused on Generative Artificial Intelligence. Generative Artificial Intelligence is a branch of Artificial Intelligence (AI) that focuses on content creation, enabling a "more interactive way of interacting with information" and data. Some of the most well-known examples of generative artificial intelligence include ChatGPT, Midjourney, or Bing, which demonstrate the potential of this technology for automatic content generation. In the past few weeks, Google Cloud has released up to ten online free courses related to Generative Artificial Intelligence. The introductory courses are suitable for any level of technical knowledge and can be completed in minutes. Others, though fewer, are intended for intermediate levels. The courses are available and accessible to anyone interested in learning. After each video, there is a short quiz to validate what has been learned. AI OF THINGS How to start programming in Artificial Intelligence: languages, tools and recommendations January 18, 2023 Introduction to Generative and Responsible Artificial Intelligence The learning path in Generative Artificial Intelligence designed by Google Cloud includes a general introduction to this field. It also includes image generation, and language models such as LLM. Furthermore, more specific topics are addressed, such as Google Cloud's Vertex AI platform for building, training, and deploying machine learning models. There's also Generative AI Studio, a tool that allows prototyping and testing of generative models. Among the offered courses, Introduction to Responsible AI focuses on the responsible development of Artificial Intelligence. This microcourse addresses the importance of data privacy and ethical considerations in all phases and processes of model development. It also explains why we need ethical Artificial Intelligence systems to achieve trusted AI. Google Cloud's course on Responsible Artificial Intelligence emphasizes the importance of incorporating ethical considerations in data and throughout the development stages of AI models. While there are numerous options to get started in Artificial Intelligence, Google Cloud's offering is an excellent starting point for understanding the foundations of generative Artificial Intelligence. This knowledge is useful for adopting these tools capable of improving our work processes and making us more productive and efficient. It also serves as a stepping stone to continue learning about Artificial Intelligence. AI of Things 5 free online courses to learn IoT (Internet of Things) in 2023 August 3, 2023 The 7 principles of Google for responsible AI Within this course, Google's 7 principles are also explained to ensure Artificial Intelligence models: Be socially beneficial. Not create or reinforce biases or prejudices. Be built and tested for safety. Be accountable to people. Incorporate privacy protection principles. Maintain high scientific excellence standards. Be available for uses that align with these principles. __ Google Cloud is part of the Telefónica Tech partner ecosystem, the network of alliances that allows us to develop the most advanced solutions on the market for our clients. Featured image from Freepik.

Typosquatting is a type of cyberattack that involves creating a domain name that is very similar to that of a well-known, legitimate website with the intention of deceiving users. This type of misleading domain name can also be used in e-mail addresses to make them appear legitimate to the naked eye, but which are fake. Typosquatting is a combination of the words "typo" and "squatting". The attacker can exploit common typos, misspellings or typing errors to carry out the deception. These errors may omit or change the order of letters. They can also substitute characters, replacing visually similar letters. Anything to create a misleading domain name. For example: Change an "l" or an "i", the "o" for a "0" (zero) or use "rn" instead of an "m". Register the same domain name but with a different extension, such as ".co" instead of ".com". Use a domain name with a similar appearance, such as goggle.com instead of google.com In addition, "in this type of cyber-attacks it is very common to use alternative spellings or words with double spelling and also the use of special characters, such as hyphens", explains Susana Alwasity, Threat Intelligence Team Lead at Telefónica Tech. In this case, for example: If the legitimate domain is bankXonline.com a typosquatting could be bankX-online.com In either case, the attacker's purpose is to trick users into visiting the fake site believing they are on the legitimate website. It is from such a website (which may be the same or even a duplicate of the original site) that attackers can distribute apps and malware or steal information such as login credentials, bank card numbers or personal information. How is typosquatting used in cyberattacks? Typosquatting is a popular technique used by cybercriminals to launch different attacks, including: Phishing attacks: attackers can create a fake login page that looks like the page of a legitimate website. When users type their login credentials into the fake page, the attacker gets hold of them to use them for malicious purposes. Malware distribution: Attackers can create a fake website that prompts users to download a file or software. When users download and install that file, they are actually unknowingly installing malware on their computer or device. Ad fraud: Attackers can create a fake website that generates advertising revenue by tricking users into clicking on ads. The attacker earns money for each click, even if the ads are irrelevant or harmful. "In addition to the theft of personal information, which can lead to phishing attacks, typosquatting can also be aimed at redirecting the domain to another destination or blackmail and reputational attacks against companies or individuals," explains Susana. The case of the Icelandic national pólice An example of a phishing attack based on typosquatting took place in Iceland in 2018. Then, cyber attackers used a domain name similar to the official domain of the Icelandic national police (Lögreglan, in Icelandic) to deceive citizens. In this case, the attackers registered a domain that replaced the "l" with an "i" (logregIan.is instead of logreglan.is), making it appear at first glance to be the legitimate domain of the country's police. But it was not. As in the previous paragraph, in the email the "i" in the URL was capitalised ("I") to make it look like an "l". At first glance, and taking advantage of the fact that our brains sometimes read words that are not words, many recipients did not detect the deception. Converting the text to small caps reveals the deception: what looks like a lowercase "L" is actually a capital "i". They then used that domain to create a fake website that looked exactly like the legitimate website. And they sent phishing emails asking the recipient to access that URL and enter personal information. The full story and analysis of the attack can be found at Police Phishing Attack Targets Bank Credentials. How to detect and protect yourself from typosquatting? Often, as in the case of Lögreglan, it is not easy to detect and protect yourself from typosquatting. But following these recommendations from our experts at Telefónica Tech helps to reduce the risk: Look at the URL before accessing a website or the sender's email extension when it is an email: look for spelling mistakes or other suspicious elements in both the domain name and its TLD extension (.com, .es,.co...). Manually copy and paste the URLs of links received by email: this prevents the malicious destination URL from being hidden under a linked or anchor text. If in doubt about what is actually written in a URL or email address, copy and paste it into a text processor such as Word: changing the font helps to detect visual deception because some fonts reveal the differences between characters better than others. It also helps to convert the text to capital letters. Word also detects the language, which is very useful when typosquatting using letters of the Cyrillic alphabet. Although they look the same, the letters 'A' and 'J' of the Cyrillic alphabet are different characters from the 'A' and 'J' of the Latin alphabet. Use a password manager: password managers automatically enter access or login credentials only on legitimate sites, where the credential was generated. Install antivirus software: they are useful for detecting and blocking malicious websites that could be used in typosquatting attacks. Don't trust the little padlock 🔒 in the browser bar: at first glance it reveals neither the authenticity of the certificate, nor who it belongs to, nor its intentions. Enable two-factor authentication: two-factor authentication adds an extra layer of security, making it harder for attackers to steal login credentials on websites or apps. Enable Google Passkeys: This is a Google identification or login method that combines the benefits of password managers and two-factor authentication in the same process. It is important to check every little detail in a URL and to be suspicious, no matter how small the error may seem. It is advisable to invest time in prevention, as the consequences can be harmful and irremediable. -Susana Alwasity, Telefónica Tech. How does Google Passkeys protect against typosquatting? Google Passkeys generates unique and complex passwords for each website the user visits. When the user visits a website, Google Passkeys automatically fills in the login credentials, such as username and password. With Google Passkeys, there is no need to remember or type the password on apps and websites, minimising the risk of the user mistakenly typing their login credentials on a fake website. Cyber Security How language puts business Cybersecurity at risk June 1, 2023 Continuing with the example above, if a user trying to visit google.com mistakenly ends up at goggle.com Google Passkeys will not work because there is a difference in the domain. So it will not automatically enter the login credentials. If this happens, it is best to leave the website, without trying to enter the credentials by hand. Conclusion Typosquatting is a cyber threat that can result in identity theft, account theft, financial and reputational loss, or lead to ransomware, among other possible consequences. Therefore, it is always important to pay attention to URLs and email addresses that may be suspicious or of unknown origin, in order to minimise the risk and protect yourself from this type of cyberattack. Featured image: Freepik.

Throughout its history, Artificial Intelligence (AI) has experienced ups and downs: periods when it received more attention and resources, and periods of disillusionment and stagnation. These periods of waning interest in Artificial Intelligence are known as AI-winters. Two AI winters have been identified in the past 50 years, and we are faced with the challenge of avoiding a third one. Consequences of an AI-winter During AI-winters, disillusionment with Artificial Intelligence translates into widespread disinterest. This disinterest leads to a reduction in attention and funding for research and development. In those periods that last years, there are few significant advancements. And the few that do occur are disappointing. Even after a moment of high enthusiasm, in an AI winter, Artificial Intelligence fades away from conversations and media coverage. Currently, Artificial Intelligence is experiencing a "Cambrian explosion" that some describe as hype or even a bubble. In any case, we are in a period of high expectations, the complete opposite of an AI winter. And precisely because it is a known pattern, the inevitable question arises: Are we on the verge of a third AI winter? AI-winters throughout history Experts have identified two AI-winters. Both occurred after notable advancements and moments of industry, media, and public excitement: Image generated with Bing First AI-winter, late 1970s and early 1980s: During this period, expectations for Artificial Intelligence were also high. However, the advancements did not live up to the exaggerated promises made by science fiction. As a result, there was a significant decrease in funding and interest in research and development of Artificial Intelligence. Second AI-winter, late 1980s and early 1990s: After the first AI winter, interest in Artificial Intelligence resurfaced. Once again, expectations exceeded achievements. The lack of significant progress and the gap between expectations and reality led to another period of disillusionment and disinterest. In 1996, IBM's supercomputer Deep Blue defeated the reigning world chess champion, Gary Kasparov, for the first time. What is AI-winter and how to avoid it Factors that could lead to a 'Third AI Winter' Some skeptics do not rule out the possibility of a third AI winter occurring after the current period of high expectations. This is mainly because new variables come into play this time, including those related to privacy, security, and ethics. This is because Artificial Intelligence is not only finding applicability in businesses this time. It is also proving useful for the general public, such as in the case of digital assistants or Generative Artificial Intelligence, two accessible forms of AI for end users. The widespread applicability of Artificial Intelligence should mitigate the occurrence of the next AI winter, but there are factors that could contribute to it. And the first one is fear. Fear: As Artificial Intelligence becomes more advanced and capable, fears arise, and news spreads regarding concerns and fears about its impact on society: fear of uncontrolled AI, job loss, invasion of privacy, lack of transparency... and the ever-present dystopian scenario. Mistrust and skepticism regarding technology can arise from these fears. However, there are more factors that could lead to a third AI winter: Restrictive legislation around Artificial Intelligence: If excessively restrictive or ill-conceived regulations are implemented, it could hinder research and development of Artificial Intelligence, limiting innovation and progress. Scarcity of high-quality data: Artificial Intelligence relies on large amounts of data, which are used to train and "teach" algorithms. If there is a lack of relevant and high-quality data in certain domains, or if the data does not consider demographic and social differences, it could hinder the development of reliable Artificial Intelligence models. Technical limitations: Limited computational power, poor energy efficiency, lack of scalability of algorithms, or technical phenomena such as hallucinations in Artificial Intelligence could slow down its progress. AI OF THINGS How to start programming in Artificial Intelligence: languages, tools and recommendations January 18, 2023 Keys to avoid AI-winter Balanced legislation: Regulations should address legitimate concerns around Artificial Intelligence (including those related to privacy, security, and non-discrimination) without hindering its development and potential benefits. Collaboration between lawmakers, AI experts, and the industry is essential to achieving this balance. Support education and technological advancements: Investing in research and development to drive significant technological advancements requires fostering academic research and collaboration between industry and institutions. It is also critical to educate children and young students. Promote trustworthy Artificial Intelligence: It is essential to address concerns regarding privacy, security, and social impact. Ethics, transparency, explainability, along with responsibility and proper governance, are indispensable principles to avoid an AI-winter. Although predicting the next AI winter is difficult, it is necessary to learn from the past and take measures to maintain sustainable progress in Artificial Intelligence. Only in this way can we avoid a third AI winter and harness the full potential of the progress offered by this technology. Featured image generated with Bing.

Climate change is considered the greatest challenge of our time. Its effects range from desertification and droughts to floods and rising sea levels. Some of its most visible consequences are natural disasters, disruptions in food production, and impacts on energy markets. However, in this scenario, next-generation digital technologies offer solutions to combat climate change and mitigate its consequences: Artificial Intelligence, Cloud, Big Data, Internet of Things (IoT), or ultra-efficient 5G connectivity are some of the enabling innovations of sustainable digital transformation.. They can help us decarbonize the economy, optimize the use of renewable energy, and protect natural resources. Sustainable digitization for green transformation At Telefónica Tech, we are committed to developing digital solutions that protect, optimize, and reuse natural resources with minimal environmental impact. Almost two out of three solutions in our portfolio carry the Eco Smart seal, verified by AENOR. The Eco Smart seal identifies products and services designed to drive green digitization. This results in reduced water and energy consumption, promoting the circular economy, and lowering emissions that contribute to the greenhouse effect. Furthermore, our solutions promote energy efficiency, sustainable agriculture, and efficient transportation. Next-generation digital technologies can contribute to a 20% reduction in CO2 emissions by 2050. Source: Accenture & World Economic Forum. Blockchain Rethinking consensus for a more sustainable Blockchain: from PoW to PoS April 5, 2023 The impact of next-generation technologies The application of next-generation digital technologies has the potential to reduce global emissions by 15% to 35% in the coming years. These technologies enable improved management, control, and real-time action in various sectors, such as industry, energy, and public utilities. Image by Freepik For example, when our digital technologies are applied to: Water supply: they can optimize distribution and reduce losses, which is particularly relevant in a context of water scarcity due to climate change. Infrastructure, such as natural gas, to reduce leaks and greenhouse gas emissions, optimize energy distribution, including renewable sources, or public lighting, among others. The agricultural sector, which is highly exposed to the increasing impact of climate change. They enable smart and precision farming, optimizing the use of resources such as water and chemicals, thus reducing costs. Workspaces, transforming the way we work: they reduce daily commutes, energy consumption, and associated CO2 emissions. Additionally, digitization of documents and reduced paper usage have a positive impact on the environment. AI of Things Key ingredients for today's Smart Cities January 31, 2023 Towards a sustainable and resilient future in the face of climate change Sustainable digitalization has emerged as a powerful tool to combat climate change and its consequences. Through the implementation of these solutions, we can: Protect our natural resources, such as water. Optimize operations, logistics routes, and industrial and production processes. Reduce polluting and greenhouse gas emissions. Generate opportunities for progress for all. Therefore, it is essential to continue driving technological innovation and fostering collaboration between the public and private sectors. This will enable a successful transition towards a more sustainable and resilient future in the face of climate change. Featured photo: Nikola Jovanovic / Unsplash.

Cybersecurity is crucial for businesses and organizations of all sizes and sectors. Cyberattacks can have severe or even fatal consequences for businesses, such as data loss, operational disruptions, or regulatory non-compliance. They can also directly impact revenue, damage reputation, or undermine employees, clients, and suppliers' trust. For these reasons, executives must understand the significance of Cyber Security for companies and take appropriate measures to protect their digital assets. And the only way to achieve this is by speaking the same language. However, that is not always the case. The language problem in Cybersecurity On the contrary, according to a recent study, 44% of executives surveyed do not prioritize Cybersecurity in their companies. This is due to the confusing language used in this field. Specifically, because "the language used is confusing and hinders threat understanding," as reported by Europa Press. This is despite the fact that 45% of executives from large companies in Spain know cyber threats are the "greatest danger" their company can face. One-third of the surveyed executives stated that they do not understand the meaning of 'malware' (malicious software), and almost another third do not comprehend the term 'ransomware' (data hijacking). Cybersecurity is a complex and technical subject. However, the language barrier is "universal in other professions," says Sergio de los Santos, Head of Innovation and Laboratory at Telefónica Tech. "If we aim to be precise, we risk being too technical and distant. If we are too simplistic, we may trivialize the problem. Finding a middle ground is challenging but possible," he explains. Cyber Security Pay When You Get Infected by Ransomware? Many Shades of Grey May 9, 2023 How to overcome the language barrier To overcome the language barrier and professional jargon in cybersecurity, it is crucial to communicate effectively. This applies not only to executives but also to the general public, including young individuals. Using clear, accessible, and honest language. Avoiding technical terms and professional jargon. Explaining concepts simply. Using examples and real-life cases to illustrate the risks and importance of protecting company systems and data. Furthermore, to enhance understanding and raise awareness about the importance of Cybersecurity, experts can conduct training courses and workshops targeted at executives. These sessions can provide: Clear and practical risk information. Security recommendations and best practices. Real demonstrations of malicious actions and attacks. Explanation of companies' measures to protect themselves from cyberattacks. Training on the solutions, tools, and resources available to companies. Cyber Security experts can also collaborate with companies' communication departments to create communication materials about cybersecurity that are clear and accessible. These materials can include texts, infographics, explanatory videos, and other resources that help executives and employees better understand risks and security measures. CYBER SECURITY Cybersecurity: “black swan“ events in a connected world March 21, 2023 Beyond language: Cyber Security importance for businesses Cybersecurity is an essential element for protecting the data, information, processes, and operations of companies against malicious attacks. It also encompasses technological and computer systems, mobile devices, and communication networks. Although 100% security is never possible, the most effective way to ensure maximum protection is through professional Cyber Security services. It is also critical to apply security best practices and provide training and awareness to employees to ensure the highest level of protection. Above all, executives must understand the significance of cybersecurity beyond language, as it is relevant to all aspects, including business continuity, of the company. Cybersecurity must be a strategic and corporate priority. Featured photo: Pressfoto on Freepik.

Google’s Passkey offers users the possibility of using an access key to identify themselves on websites or apps without typing their username and password. Google explains that the passkeys replace traditional (and burdensome) passwords. A new mechanism in addition to Google’s “Skip password when possible” function, such as accepting a notification from another device. Passkeys are an alternative to username and password credential systems. The end of passwords is a desire and a necessity that many users have been demanding for years. Not only for convenience, but above all, for security. Passwords are "primitive" and have too many flaws. What is a passkey? n this context, when we talk about a passkey, we mean a digital credential that identifies us to a system (such as a web page or service, or an app) using a PIN or biometric identification. That is, instead of authenticating ourselves by typing something we know (username and password) we also identify ourselves with something we are or have: Drawing an unlock pattern on our device. Type a PIN number. Using our fingerprints. Identifying ourselves by our faces. The result is similar to when the operating system or web browser saves passwords. But with an additional layer of security that verifies the identity of the person trying to use those saved credentials. CYBER SECURITY Cybersecurity: “black swan“ events in a connected world March 21, 2023 How does Google Passkey work? Unlike username and password-based credentials, passkeys use asymmetric or public key cryptography. In other words, the credential is made up of two mathematically related keys: The public key, which is stored on the website or in the app. The private key, which is stored on the user’s device. Since the website or app only stores the public key, password theft or leak does not expose the user’s credentials. An attacker with only the public key cannot do anything with it: neither identify the user nor access the user’s account. This is one of the reasons passkeys are more secure than passwords. Even with the device that stores the private key (the other “half” of the key) an attacker will still have to circumvent one of the identification systems we mentioned —PIN, unlock pattern, fingerprint, or facial recognition. Improved phishing protection Passkeys keeps a record that links each private key to the app or website that holds the public key, unique in each case. So a passkey is not activated when accessing a malicious site, because can only be used on the website or app where it was generated. Passkey are based on the FIDO standard and work on Android, Chrome, Windows, Edge, macOS, iOS, Safari, etc. … Passkey is based on the FIDO (Fast Identity Online) specification of the FIDO Alliance that applies more robust authentication factors than passwords. Its purpose is to promote a common mechanism that saves us from remembering or managing passwords. However, above all, it aims to strengthen security by better protecting users. This includes, for example, preventing attacks designed to steal passwords and access credentials, such as phishing attacks. Goodbye to the two-factor authentication (2FA) Passkey adds an additional benefit for users: passkeys make two-factor authentication (2FA) through mechanisms such as SMS codes, security calls or email links unnecessary. Example of two-factor authentication (2FA). Photo: Photo by Ed Hardie on Unsplash Two-factor authentication is now an essential mechanism to strengthen security and protect against credential theft or unauthorized access. However, it is also cumbersome because it requires taking a call or waiting for an SMS or email with a numeric code or link. How to set up Google Passkey To use Passkey the Android, iOS, Windows or macOS device must meet a series of minimum requirements that can be checked here. To activate Passkeys: Go to g.co/passkeys and log in with your Google account. Click on the Create passkey option. Choose which device you want to create the passkey on. Once created, the passkey is saved on the selected device. It can then be used to log in to Google without typing the username and password. CYBER SECURITY Artificial Intelligence, ChatGPT, and Cyber Security February 15, 2023 It is critical to note that once a key is created it can be used by anyone who has access to that device. For example, another person who has your mobile and knows the PIN or unlock pattern. The passkey is stored on that device and cannot be removed, although it can be shared with other devices belonging to the same user. In case of loss or theft of the device that stores the passkey, it will be necessary to access the Google account (this time with the usual password) and delete the keys associated with the lost device. Featured photo: Florian Berger / Unsplash.

Raspberry Pi is a popular computer widely used among developers, students and fans of computing, robotics, and gadgetry. Among its virtues are its low cost (a basic kit costs about 20 euros), versatility to run a wide variety of applications and solutions, and a huge community of users who share projects, tutorials, and all kinds of content to get the most out of it. The most affordable basic configuration of Raspberry Pi is not a powerful computer. Although its capacity will depend on the model chosen, its configuration, peripherals and added components, and the modifications made by the user. Even in their most basic and affordable models, Raspberry Pi boards can run programs with multiple purposes and applications. However, in any of its models, even the cheapest ones, Raspberry Pi allows running applications with multiple purposes, including the control of home automation installations, robotic systems or as a web server. Raspberry Pi 1 Model A+. Photo: RASPBERRY PI The Raspberry Pi boards, however, are not as efficient as they could be when it comes to running algorithms and Artificial Intelligence models, regardless of their power. Something that Sony wants to solve. Sony integrates its Edge AI Aitrios platform on Raspberry Pi boards In order to change this, Sony has announced a "strategic investment" to help "drive the development of Edge AI solutions" by integrating its Aitrios platform into Raspberry Pi boards. In this way Sony enables AI capabilities on this popular computer for everyone. This integration will allow Raspberry Pi users to use the Aitrios platform to run their own Artificial Intelligence solutions; with customized developments tailored to their needs, whether domestic or industrial. Aitrios provides Raspberry Pi with increased capacity to process data and AI models in real time. By incorporating this Sony technology, Raspberry Pi devices equipped with Aitrios are more efficient at processing and analyzing data locally, in the same place where that data is generated and where it is needed: at the edge of the network and without the need to send it to a data center or a Cloud platform. Raspberry Pi boards are increasingly used in the industry due to their low cost, versatility and ability to run a wide variety of applications and solutions. Photo: RASPBERRY PI. As we saw in a previous article, processing data and running AI models at the edge (Edge AI) is especially useful when an immediate response is required and without relying on an internet connection. For example: For the control of drones and self-piloted robots, or for image or voice recognition. When an IoT project is deployed in an area without network coverage or in an isolated environment, without connectivity. Sony Aitrios platform for IoT devices Sony's Aitrios platform enables data processing and efficient execution of AI algorithms and models in IoT devices. Aitrios is a complete hardware and software solution, scalable and flexible, Sony explains. It can be adapted to a wide variety of IoT devices and applications and is available in different architectures, such as SoC processors or peripheral modules. It can be controlled with different operating systems. These features should facilitate its adoption by the Raspberry Pi user community by facilitating the development and implementation of new projects. In the process, Sony gains for Aitrios a potentially huge user and developer base. Local machine vision to monitor retailer inventory while protecting customer privacy is an Edge AI use case. Photo: SONY. On the hardware side, Aitrios uses an ASIC (Application-Specific Integrated Circuit) type processor. As an advantage over CPU or general-purpose processors, ASIC processors are especially efficient at performing the task for which they are designed. In this case, the Aitrios processor is specifically designed to run and train ultra-low latency machine vision and machine learning models, which will improve the efficiency of Raspberry Pi computers to process and analyze data locally. Featured photo: Karminski / Unsplash.

This week we are at Advanced Factories, the annual reference meeting on innovation and industrial automation, robotics, and digitalized industry or Industry 4.0. At Telfónica Tech, we are sharing our knowledge and experience. We are also showcasing technologies that enable process automation and digitalization of the industrial sector, driving efficiency and productivity. “Industry 4.0 consists of integrating technology into the process to produce more and better at lower costs.” —Darío Cesena, Geprom part of Telefónica Tech. To demonstrate how new generation digital technologies improve industrial competitiveness and how they are applied in the sector, at Advanced Factories we have four demos that incorporate our main enabling technologies of Industry 4.0: IoT sensors to collect real-time data. 5G and NB-IoT connectivity to provide high-speed and ultra-low latency connection. Cloud and Edge Computing to store and process large amounts of data. Industrial management software and data analytics to optimize process management. Big Data and Artificial Intelligence to obtain insights and improve efficiency. Cyber Security to protect the entire industrial process. Our interactive demos at Advanced Factories 1. Smart Lego Factory, an intelligent process factory Adapted to an event context, we built a process factory with Lego. Process factories produce goods that cannot be broken down into their elements. This would be the case, for example, with detergent or soda. These types of factories have highly automated processes. Generate lots of data. Capturing and processing data allows process improvement, cost savings, and increased efficiency and profitability. The Smart Lego Factory demo allows visitors to see and interact with our IoT/MoM Legato platform for manufacturing process management (MES). Legato provides real-time information about factory performance. This solution allows to know any parameter, both in the production process and in the business layer. As long as that process is sensorized, generates data, and is connected. 2. Fab Lab 4.0, a smart factory for discrete manufacturing Also with a scale model, we showed our visitors how to apply our knowledge and technology to a discrete manufacturing process. This is the type of factory that combines different parts to achieve the final product, such as a car or toy factory. These are usually factories with more involvement of operators, where knowledge resides, than machines, which generates less data. In this case, our MES/SGA Objective platform does not focus as much on data capture as on guiding the operator and monitoring the process. It also monitors the parts used, and the final result. For this scenario, we have a small toy helicopter factory at the stand that visitors can assemble following the instructions on a screen. At the same time, MES software tracks the steps and parts used. Upon completing the assembly, the MES software assigns a serial number to each finished toy to ensure traceability of the final product: who assembled it and when, how long it took, what parts were used, etc. Blockchain would add an additional guarantee of authenticity and immutability of that information. In this demo, the Legato software controls the production, monitoring in real time and making decisions to improve the efficiency and quality of the manufacturing process. 3. Connected preventative safety with Livall smart helmets At our booth, we also have a connected worker helmet. It is based on the same approach as Livall's connected helmets for motorcyclists or cyclists. For use in industrial environments, the helmet is equipped with sensors that measure air quality and ambient temperature. It also has an accelerometer to detect impacts and sudden movements. Thanks to these sensors, Livall's helmet can anticipate industrial risks such as environmental toxins or poor air quality. In addition, it can alert in case of detecting impacts or falls of the worker. The NB-IoT connectivity of the Livall helmet allows its use in large facilities such as a mine or a petrochemical plant. The data generated by the helmet is sent anonymized to a platform that processes it; for example, to activate safety measures. 4. Spot, the 5G-connected ‘robot dog’ for industrial environments monitoring Spot, the ‘robot dog’ by Boston Dynamics, is the perfect example of the possibilities offered by self-piloted robotics in the industrial sector. The Alisys unit that accompanies us these days at Advanced Factories incorporates 5G connectivity to communicate with our Edge Computing solution. 5G connectivity, in addition to telecontrol, allows the data captured by the sensors embedded in Spot to be sent: a thermal camera, a 360 vision camera, and control of a robotic arm. In self-piloted robotics, such as automatic guided vehicles or AGVs, drones, or other machinery, 5G connectivity provides: Ultra-low latency, almost imperceptible, essential for the robot to move and interact with the environment in real time. High capacity to transmit and process data, such as images captured by cameras. For the industrial sector, we are already defining use cases for self-piloted robots like Spot. Although not directly related to production processes, they have real applications in factories: In a large-scale car factory to inspect the facilities, Spot can examine for thermal differences or to identify objects. In a waste processing and recycling center, Spot can identify health risks in the area where the raw material (waste) is stored, such as toxic gases or hazardous materials. The same technologies that enable Spot (5G connectivity with network slicing, Edge Computing, sensorization) can also be applied to other purposes: logistics, surveillance, or goods movement. Other self-piloted robots, such as drones or AGVs, can also benefit from these technologies. The knowledge and experience of our experts and clients In Advanced Factories we also participate with lectures and talks of our experts and customers, to tell first hand their experiences and projects: Comprehensive digitization of production processes applying Artificial Intelligence: The case of Stolt Sea Farm Darío Cesena (Geprom part of Telefónica Tech) and Jorge Juan Alfonso (Stolt Sea Farm) Darío Cesena (Geprom part of Telefónica Tech) and Jorge Juan Alfonso (Stolt Sea Farm) spoke about aquaculture farm digitization. They highlighted how data is changing industrial manufacturing to increase productivity, meet customer demands, and better manage operational processes. A company's data is another asset," says Darío Cesena, Geprom part of Telefónica Tech. To achieve this, it is necessary to collect and analyze information. Artificial Intelligence models allow for insights and optimizing production, as we do in Stolt Sea Farm's aquaculture farms. By applying connectivity solutions, Artificial Intelligence, Big Data, and Cyber Security, which make industrial processes more efficient, Stolt also can predict supply and demand for their products. This is an especially important considering that some species take years to reach their desired size. Stolt provides "quality service and products to its customers while also promoting innovation in its own activity and in the food sector," explained Jorge Juan Alfonso, Food Operations Manager at Stolt Sea Farm. The intelligent helmet for preventive safety management of industry workers Alfredo Serret (left) from Telefónica Tech and Manu Marín from Livall Alfredo Serret (Telefónica Tech) and Manu Marín (Livall) talked about connected helmets in the industrial sector. Marín took a few minutes to discuss the beginnings and motivations of Livall, a platform built to "put the benefits of intelligent mobility at the service of people." From that idea other variants and applications emerged, such as a helmet for skiers and the connected helmet designed for accident prevention, which we showed at our Advanced Factories stand. Although the helmet aims to provide "preventive safety to avoid accidents," it also can sensorize a factory, saving large costs," explained Marín. "The digitalization of the industry benefits the people at the center of the process as well." - Alfredo Serret, Telefónica Tech. Both participants agreed that Livall's industrial helmet has many possibilities and use cases for the digitalization of the industry to also benefit "the people who are at the center of industrial processes," explained Alfredo Serret. Quality and maintenance: A leap in competitiveness supported by technology Javier Martínez Borreguero (Telefónica Tech) Javier Martínez Borreguero (Telefónica Tech) participated in a roundtable discussion on predictive maintenance with Artificial Intelligence. Borreguero listed some benefits of industry digitalization: Resilience. Sustainability and positive impact. New business models. "In the next five years, 95% of quality and maintenance management processes in the industry will incorporate Artificial Intelligence and massive connectivity," he added. These are available technologies that we can incorporate into the industrial sector to tackle challenges in quality and maintenance management. "5G connectivity and Artificial Intelligence are realities. They are available technologies. The question is: are they integrated into your production processes?" - Javier Martínez Borreguero, Telefónica Tech. AI of Things Satellites with 5G technology to provide IoT coverage worldwide April 10, 2023 Turn-key solutions for Industry 4.0 At Advanced Factories we share our complete vision of a digitized factory, end-to-end: from the entry of raw materials to the exit of the final product. 5G connectivity, Cloud, Cyber Security, Big Data or Artificial Intelligence models, among other enabling technologies, allow us to address any need across the entire spectrum, from the factory floor to data analysis. Further, we develop digitalization projects that connect factory software with business layers using our industrial knowledge and sensorization. As a result, we can provide customized solutions to meet the needs of each customer.

Edge AI refers to the execution of AI algorithms near or on devices such as wearables, mobiles, cameras, IoT (Internet of Things) sensors or edge servers, which the ability to analyse and process data. In real-time and without depending on a server on the internet. In contrast, the use of Artificial Intelligence in Cloud (Cloud AI) requires sending data to a data center or Cloud platform where they are stored and processed. It usually requires a permanent, robust, and capable connection. Edge AI is therefore closely related to Edge Computing. Both concepts refer to processing and analysing data at the edge of the network. That is, processing takes place in close proximity to or even on the very devices that generate the data. With Edge AI, response times are shortened, and efficiency and security are improved when executing Artificial Intelligence models on Edge devices. Edge AI features In order for Edge AI to be possible, analytical models and AI algorithms must be able to run on local servers or on devices equipped with processors with a certain computational capacity, as described in the article Edge Computing and Machine Learning, a strategic alliance. However, Edge AI devices often have limitations in terms of computing power, memory, and storage space for data. Also, autonomy if they run on a battery, depending on the case. This limitation may require optimizing algorithms and, depending on their purpose, using specialized hardware. Optimising algorithms by applying techniques such as reducing the complexity of models, quantifying parameters, or eliminating unnecessary connections in the neural network (pruning) to speed up its operation. Also, using of specific architectures for low-power devices. Specialised hardware that makes use of specific processors for AI applications, such as computer vision and neural network inference processors. AI-focused ASIC (Application-Specific Integrated Circuit) chips, such as the IBM AIU processor, offer high performance and low latency compared to general purpose processors or CPUs. Security is also a critical aspect for Edge AI devices. Processing and analysing data on a local device reduces the risk of data exposure. But Edge AI devices are also vulnerable and equally exposed to cyber threats and attacks. The use of Edge AI can also have privacy implications for users, depending on their function. Therefore, Edge AI must implement mechanisms for encryption, authentication, anomaly detection and privacy management. Cloud Latency and Edge Computing: Why is it important? September 20, 2022 Differences between Edge AI and Cloud AI As mentioned above, the main difference between Cloud AI and Edge AI is in where the algorithms runs: In Cloud AI, data storage and processing happens on conventional, centralised Cloud servers, often managed by a Cloud provider. In Edge AI, data and algorithms are stored and run on hardware peripheral to the network; from wearables to vehicles to IoT devices to Edge servers, such as Snowball de AWS. This difference means that each approach has its advantages and disadvantages as we will see more in a future post, but they can be briefly summarised as follows: Cloud AI Advantages: it usually has a greater capacity and computing power, which allows it to process and analyse large amounts of data. As a cloud platform, the power and capacity can be scaled up or down as needed. Disadvantages: The need to transfer data can cause speed, security and regulatory, data residency or privacy issues. Physical distance of hundreds or thousands of kilometres or network congestion can slow communications and increase data exposure. Edge AI Advantages: requires less bandwidth and has almost imperceptible latency. It offers immediate response and increased data security, but also has an impact on users' privacy. It can operate in remote areas or isolated environments without connectivity. Disadvantages: As mentioned above, limited computing power and memory can reduce the types and complexity of AI models they can run. The need to optimise algorithms and use specific hardware can increase development and deployment costs. Edge AI applications Edge AI can be applied in a variety of sectors. Some of the most obvious applications include security surveillance, voice assistants, Smart Industry or wearables. Some use cases would be: Security cameras with machine vision capabilities that analyse image content in real time to identify suspicious objects or people, events or behaviour. Voice assistants learn to recognise speech locally to detect when to activate or to respond to simple instructions. In Smart Industry, where sensors or vision systems monitor the quality of production or logistics processes or products, such as the demo we showed together with AWS at MWC. Wearables and medical devices, such as heart rate or glucose monitors, to analyse patient data in real time and alert on any anomaly. Edge AI can also be applied to driver assistance systems (ADAS). Or in autonomous cars, to process data captured by vehicle sensors, such as cameras or accelerometers, to detect and respond to traffic conditions. Conclusion Edge AI is a suitable approach in cases where data needs to be analysed and processed and an immediate response is required. Without delay due to latency or insufficient connectivity or bandwidth, while maintaining data privacy and security with the right implementation. Edge AI is still in its infancy with the continuous improvement of processing and storage capabilities in IoT devices and new developments in AI-specific hardware, such as AIU processors, Edge AI is still in its early evolutions. The combination of Edge AI and next-generation connectivity, such as 5G and LPWA or NB-IoT via satellite, will accelerate innovation and has the potential to extend the reach of AI-enabled solutions to a wider range of industries and regions. Featured photo: Luke Chesser / Unsplash. Apple Watch is an example of an Edge AI (consumer) device capable of processing data and executing AI models locally.

📌 In July 2023, Sateliot and Telefónica brought 5G network coverage to space for the first time ever using a conventional SIM card integrated into Telefónica Tech's Kite platform. This paves the way for global IoT connectivity. Find out more. During the last edition of MWC, our colleague Javier Zorzano participated in the "5G IoT Summit: Hybrid NB-IoT and Satellite Solutions" alongside Shahbaz Ali, from Sateliot. In their talk, Javier and Shahbaz discussed the benefits and challenges around satellite connectivity for IoT devices. This technology, which we are jointly developing, expands and complements our portfolio of NB-IoT connectivity solutions via 5G and LPWA networks. This way, we are configuring a hybrid solution, with both terrestrial and non-terrestrial (NTN) satellite networks, to offer our customers global NB-IoT coverage. "Only 30 percent of the world’s surface has coverage from terrestrial networks" according to IoT For All. For this publication, satellite connectivity was one of the "dominant trends" at Mobile World Congress 2023. "The next step in NB-IoT connectivity is to provide global coverage, worldwide. And that step is what we are taking now." —Javier Zorzano (Telefónica Tech) The growing number of industries and sectors adopting IoT solutions worldwide makes it necessary to develop this hybrid IoT connectivity that provides coverage worldwide. Otherwise, there will be more and more IoT use cases that cannot be developed due to the lack of communication. For example, for the livestock sector operating in rural or remote regions, for the logistics sector when it needs to accurately track the status and location of its goods on transoceanic routes, or for the renewable energy sector that manages wind farms or solar farms in hard-to-reach places. Convergence of terrestrial and non-terrestrial networks As explained by Shahbaz Ali during the meeting, Sateliot is developing the first 5G NB-IoT constellation of LEO (Low Earth Orbit) nanosatellites. This constellation is made up of small and efficient satellites typically located between 500 and 600 kilometers in altitude to condiv an NTN (Non-Terrestrial Network) IoT connectivity network capable of integrating into our 5G terrestrial network. Sateliot's nanosatellite recreation. Image: SATELIOT Our collaboration with Sateliot consists of developing a technological solution that includes satellite IoT connectivity to offer an affordable and transparent solution for our customers: satellite IoT connectivity based on the same 3GPP standard as 5G and NB-IoT networks. This connectivity is also compatible with the same IoT devices currently used thanks to the development and certification of hybrid connectivity modules. "Thanks to standardization, our hybrid IoT connectivity technology is affordable and scalable, and will reduce frictions when adopting it." - Shahbaz Ali (Sateliot) This way any conventional IoT device can simultaneously work with terrestrial 5G NB-IoT networks and satellite networks. So service providers "will be able to connect with the nanosatellite network using a roaming service when they need 5G coverage to offer connectivity and follow, for example, the cargo of a moving ship, the trajectory of a mountain biker or alert emergency services in the case of an accident," explains Sateliot. AI of Things 5 free online courses to learn IoT (Internet of Things) in 2023 August 3, 2023 Benefits and challenges of our satellite IoT connectivity The development of IoT connectivity via satellite provides two important benefits to any IoT solution: Global coverage in remote areas and in territories without network infrastructure or mobile coverage, helping to close the digital divide between regions. Backup coverage to reinforce mobile network coverage and to ensure service continuity in case of disruption due to incidents or natural disasters. The solution we are developing with Sateliot not only allows the use of the same IoT devices already on the market, but also the same SIM card. Whether connected through a conventional network or through Sateliot's network, connectivity can be managed through our Kite platform. Satellite connectivity managed with Kite Platform Kite Platform is our managed connectivity solution through which our customers can easily control and monitor their data line SIM cards in real time, via web or API. In this way, "our solution is equivalent to having a conventional roaming agreement, but with a satellite operator," explains Javier Zorzano. From a technical point of view, this simplifies and reduces the adoption time of this technology. From a commercial point of view, this roaming agreement is more affordable than existing solutions in the market. The first commercial pilots of satellite NB-IoT with customers are planned for the end of the year. With our technology and in collaboration with Sateliot, we address the major challenges of satellite connectivity: Connectivity management, with our Kite Platform technology. Service cost, a "very sensitive" aspect for the IoT B2B market. The massive adoption of IoT that demands coverage in places not covered by terrestrial networks. Conclusion Our partnership with Sateliot helps provide NB-IoT coverage on a global scale. It also contributes to the massive deployment of our IoT solutions and devices, especially in the B2B sector. This technological solution opens up new possibilities and use cases for IoT technology. From precise tracking of goods or fleet management anywhere in the world to the development of smart livestock and agriculture solutions in rural areas, as well as environmental monitoring projects or the management of natural resources such as water or energy. "Possibilities that we could not consider before are now on the table," concludes Javier Zorzano. Watch the talk with Javier Zorzano (Telefónica Tech) and Shahbaz Ali (Sateliot) in which they discuss the benefits and challenges of satellite connectivity for IoT devices (Hybrid NB-IoT), a solution that expands and complements our IoT connectivity portfolio. Featured photo: Stefan Stefancik / Unsplash

Cyber threats have existed since technology began to be used in companies and organizations. But the evolution of the technology world in the 21st century has changed the landscape: the famous "security perimeter" no longer exists, and our digital data and assets are located in different places and constantly moving, making it difficult to protect against threats. Mobile devices, cloud services, or the location of digital assets in changing places, sometimes outside our borders, have blurred that perimeter. This has led to a new era in which organizations face global risks. Cybercrime as a service (CaaS) Today, malicious actors have professionalized and many operate as international organized crime groups. These groups "rent out" their attack and encryption tools in affiliate models, meaning that criminals with lower levels of preparation can access powerful attack tools in exchange for sharing their profits. At the same time, the technological advance that protects organizations has been matched by malicious actors who remain at the forefront of the latest technologies and techniques. In some key legal issues, such as the practical impossibility of attributing criminal offenses in certain areas of the Internet, such as the dark web, the impunity of these actors remains. CYBER SECURITY Artificial Intelligence, ChatGPT, and Cyber Security February 15, 2023 Main threats today Among the main threats faced by organizations today are: Ransomware: Destructive attacks that encrypt an organization's data and demand ransom in exchange for the tools and secret keys that allow its recovery. Denial of Service (DDoS): Attacks aimed at stopping or deteriorating an organization's websites or systems. They can be motivated by activism, commissioned, rewarded, etc. The environment is artificially overloaded until it stops working or does so very poorly. Email-related attacks and identity theft: Phishing is one of the most used methods. Criminals send "deceptive" messages with links or malicious files that, once opened, infect systems and allow malicious actors to access valuable organization information. Data theft: Malicious actors take over large amounts of an organization's data and exfiltrate it (possibly using the company's own legitimate mechanisms) to be sold, auctioned, etc. Malware: Other families of malicious software are frequently used to harm systems (viruses), spy (backdoors, keyloggers, etc.), or profit. For example, "miners" are programs that mine cryptocurrencies in the infrastructure without the company being aware, generating economic benefits for the malicious actor. Insiders: Sometimes the "enemy is at home" and they are employees or collaborators who act out of revenge or to obtain economic benefit. How to protect yourself against these threats? For any company, SME, and organization, protection against these threats must be approached from a holistic and comprehensive perspective, considering all relevant and interrelated aspects. A solid Cybersecurity strategy must take into account both prevention and detection and response to incidents. Therefore, for companies and organizations, it is essential to: Carry out good information security management, which includes identifying the organization's critical assets, assessing risks, defining security measures, and implementing appropriate controls. Have clear security policies and procedures that establish the responsibilities and obligations of employees and other actors related to the organization, as well as how to act in case of an incident. Offer good training and awareness in Cybersecurity for all employees of the organization, so that they are aware of the risks and know how to act in case of an incident. Have monitoring and analysis systems for network and system activity that allow early detection of possible security incidents and enable quick action to minimize damage. Design a Cybersecurity incident response plan that establishes the procedures to be followed in case of an incident, including notification to authorities and the management of communication with customers and other stakeholders. Other measures that can help protect an organization against cybersecurity threats include the use of advanced technological security solutions, such as firewalls, antivirus software, intrusion detection systems, and vulnerability management solutions. CYBER SECURITY Cybersecurity: “black swan“ events in a connected world March 21, 2023 Conclusion Cybersecurity poses real threats to all organizations, and it is essential to protect a company's assets and data. Threats are becoming increasingly sophisticated and dangerous, and organizations must stay up-to-date with the latest trends and threats in the field of cybersecurity to ensure adequate protection and be prepared to effectively face them. A comprehensive security approach, including technological measures, security policies, and staff training, is essential to minimize risks. Featured photo: Stefano Pollio / Unsplash

According to data from GSMA, collected by the publication Redes & Telecom, by the end of 2022, over one billion 5G connections had been surpassed worldwide; this div will reach two billion in 2025, providing coverage to a third of the population in Europe. 5G connectivity is experiencing progressive deployment that is faster than its predecessors, 3G and 4G. Real use cases for 5G connectivity At Telefónica Tech, we are already implementing solutions to transform sectors such as industry by launching different projects that successfully leverage the advantages and enormous potential of 5G connectivity, such as: Gestamp: The smart factory of Gestamp is based on a digital twin. A digital twin consists of a virtual model of the factory that optimizes production and helps with decision-making. The physical elements of the plant are connected via 5G to generate a virtual copy of the entire factory that allows industrial processes to be validated, different scenarios to be tested, and decisions based on data to be made. APM Terminals: One of the largest operators of ports, maritime and land terminals in the world uses 5G connectivity to coordinate port traffic and improve safety through the deployment of 5G coverage at the APM Terminals terminal in the Port of Barcelona. The provision of 5G connectivity in cranes, trucks, and mobile staff allows all active actors to be located and visible in real-time, whether they are in motion or not, within the terminal. This helps reduce accidents among facilities, workers, vehicles, and goods. Navantia: The Spanish company of reference in the manufacture of advanced ships uses 5G connectivity to remotely assist maintenance officers through Augmented Reality (AR) glasses. It also uses 5G to support the shipbuilding process, including processing 3D scanning in real-time, thus optimizing its production processes. IE University: It has an immersive teaching center on its Segovia Campus that uses 5G connectivity in its implementation of virtual classes through streaming and from personal devices. This way, it can incorporate new educational resources such as Virtual Reality (VR), which allows specialized classes to be taught through immersive experiences for its students. AI of Things Key ingredients for today's Smart Cities January 31, 2023 5G Connectivity: Key Advantages The three key advantages of 5G connectivity are its transmission capacity and speed, imperceptible latency, and high concurrency of devices connected simultaneously in specific geographical areas. Capacity and speed: 5G can reach download speeds of up to 10 gigabits per second (Gbps), allowing for the transmission of large amounts of data in less time. Latency: Latency is the time that elapses from when a connection or request is initiated on one end until a response is received from the other end. For example, it is the time that elapses from when an industrial robot requests instructions to operate until it receives those instructions. With 5G, latency can be as low as 5 milliseconds, allowing for almost real-time communication. Concurrency: The high capacity and concurrency that 5G allows make it possible to connect multiple devices simultaneously, including IoT sensors and actuators: 5G supports up to one million connected devices per square kilometer. 5G technology is up to 90% more efficient in terms of energy consumption per unit of traffic. Because of its characteristics and advantages, 5G connectivity also has significant implications for other new-generation digital technologies, including Big Data, the Internet of Things (IoT), and Artificial Intelligence (AI). IoT (Internet of Things): 5G enables the reliable, secure connection of numerous devices without sacrificing its low latency. Big Data: Thanks to 5G's high data transfer capacity, it is possible to send and receive large volumes of information almost in real-time. Artificial Intelligence (AI): 5G connectivity enables automated systems to respond almost instantly. Cyber Security Consequences of a cyber-attack in industrial environments January 17, 2023

Today, March 8th, International Women's Day, we start a series of interviews with #LadyHackers from Telefónica Tech. Through their work and effort, these women are helping us become a more creative and innovative company. * * * Tell us a little about yourself: who are you and what do you do? I'm Jess Woods and I joined Telefonica Tech UK&I in October 2021 as a Senior Product Manager, which means that I'm responsible for our Cloud product strategy and roadmap. What is your specialization and how do you acquire new knowledge on a daily basis? I specialise in our Cloud services portfolio, comprising of Public Cloud, Private Cloud, Data Protection and Edge Computing. This is a set of broad and ever-changing technologies, so I am constantly learning through conversation, research and most importantly listening to others. What or who motivated you to choose a technology-related profession? I studied Sociology at university so whilst it wasn't a STEAM subject, I did a module that focussed on the impact of the ‘Internet on Society’ and it really piqued my interest. After I graduated, I secured a role in Customer Services at a locally headquartered MSP. An opportunity opened up to join a newly formed Product Management Team and I jumped at the chance to apply. Twelve years on, I'm passionate about the discipline of Product Management and also how technology can improve lives. Most of my technical knowledge comes from being curious, through constant communication with internal and external stakeholders, online training and a lot of learning on the job which I think never ends if you retain that growth mindset. Many think that not studying a STEAM subject prevents them from building careers in the technology sector but there are lots of routes available if you have the passion. What training would you recommend to someone who wants to pursue this specialty? Being a Product Manager is a diverse role and requires many skill sets so there isn't really one single training route to become one. As it's a relative new profession, there are different interpretations of the role so it may be industry specific or require different skills dependent on whether you are managing physical or software products. Personally, I really enjoyed doing a course ran by Product focus for Product Manager in Technical roles. It's increasingly important to make sure you can adopt agile approaches so any training that you can do in that space is really beneficial. It's also vital that you know your product and your market so taking vendor led training, reading industry whitepapers and research and keeping an eye on tech news are all important. Diversity encourages the search for novel information and perspectives, leading to better decision-making and problem-solving, improving the bottom line of companies. —Scientific American. Could you explain to us what the #LadyHacker initiative means to you? I couldn't be more encouraging of making the role of women in the tech sector more visible —there have been too many times where I am the only women in the room or amongst a select few. Gender stereotypes need to be broken for both, men and women. But we need society to recognise that it isn't a level playing field out there, and there is more work to be done when it comes to equity and inclusion for women. Particularly in technology professions. We can make a difference with initiatives like #LadyHacker to let more voices be heard. What do women bring to STEAM professions? Honestly, I think that women bring the same that men do to STEAM professions. We're all humans, we’re not all the same, nor do we have the same needs. But women bring energy, expertise, dedicated and determination to drive change within any STEAM profession. Jess Woods, Cloud expert at Telefónica Tech We need to work harder to ensure that our society encourages this from an early age and that when we do enter these careers that we're bought into environments that welcome inclusion and diversity. Also, we must recognise and address the need for equity. How is your experience in the work environment? I've had mixed experiences within the workplace over my career so far. Some have been not so great — one example is at a trade show one year: somebody came up to our stand and asked who the technical representative was. They were directed to me and visible scoffed in disbelieve, as I was at the time in my mid-twenties and clearly not who he was expecting to speak to. However, I have had so many fantastic experiences in my profession. I have had some fantastic mentors, built some excellent relationships and formed many friendships over my 15 years in IT. What advice would you give to the Jess Woods of 10 years ago? Ten years ago, I was two years into my career as a Product Manager. I think my advice would be to trust your instincts and that everything happens for a reason. I was hard on myself when I went through university clearing and, again, when I wasn't successful in securing a graduate role. Hard work and determination have led to be being in the same position in my career as those who were on graduate schemes, it just meant that I needed to take a different path to get there. Telefónica Tech “To be a hacker in life is to be a passionate, talented person who manages to influence the transformation of society", Carmen Alonso July 28, 2022 Telefónica Tech «We are moving towards genderless professions», María Martínez August 8, 2022 Telefónica Tech Meet #LadyHacker Karla Parra, Cybersecurity expert at Telefónica Tech June 20, 2023 Telefónica Tech #LadyHacker Tamires Abujamra is innovating at Telefónica Tech Brazil September 14, 2023

Following four intense days, Mobile Word Congress (MWC) 2023 bids farewell today until next year. Since opening its doors last Monday, attendees have had the opportunity to see the latest innovations in the field of mobile connectivity first-hand. Telefónica Tech participated in MWC 2023 with a wide range of activities this year, including presentations, demos and professional meetings on next-generation digital technologies and solutions for the digitalisation of companies at a stand that extended further than the physical space, into the metaverse and beyond. In this post we collect and summarise the main activities in which we have participated in this edition of the MWC. Demos of our digital technologies Smart Agriculture Solutions Making Smart Agro Happen, MWC2023 The Making Smart Agro Happen demo, applied to a vineyard at Bodegas Godeval, reiterated our commitment to bringing digitalization to all economic activities and sectors using solutions with the Eco Smart seal, certified by AENOR. Including agriculture, by showcasing how digitalization and new-generation technologies can improve productivity, resilience, and sustainability in agriculture. The demo included precision agriculture solutions, smart irrigation management, Artificial Intelligence algorithms to prevent diseases and pests, and the optimization of resources such as water and fertilizers. Furthermore, it was shown how Blockchain technology can certify and protect entries in the digital field notebook, enables the traceability of production processes and the certification of the origin of the products. Smart industry and digital twins Making Smart Industry Happen, MWC 2023 With the Making Smart Industry Happen demo, we show how a 'digital twin' works using technologies such as 5G, Edge Computing, data analytics, and machine learning to optimize industrial part production and make real-time decisions. The digital twin includes a robotic arm that simulates the construction of an industrial part, and its movement is synchronized with a digital representation of the part. This helps detect potential failures and improve efficiency and quality in the manufacturing process, which in turn reduces energy and material consumption, increasing profitability. Indoor Insights with Computer Vision Using C2RO's computer vision technology, which is part of our solution portfolio, and by placing cameras in our booth and applying Artificial Intelligence algorithms, we could constantly and in real time know how many people were visiting us in different areas and have knowledge of how things were unfolding. This Indoor Insights solution allows for understanding the flow and anonymous behavior of visitors, which aids in data-driven decision-making. Quality Control in Industrial IoT At the Amazon Web Services (AWS) booth, we demonstrated an example of Industrial IoT (IIoT) usage for quality control in manufacturing, production, and logistics processes (using cameras, 5G connectivity, and our Edge Computing solutions) to ensure that products and services meet the required quality standards set by the manufacturer, customers, and regulators. Talks, presentations and expert sessions Conference The Smart Factory: Manufacturing, Maintenance, and Logistics, with Darío Cesena (Geprom Connecting Industries | Part of Telefónica Tech), Pablo Martin García (NTT DATA), and Jesús Martín Tello (NTT DATA). Mobile identity APIs: the road to success. Our expert Glyn Povah, participated in a talk on Mobile Identity APIs, the next step to guarantee and protect the identity of users thanks to the mobile. This technology combines SIM-based solutions and mechanisms such as facial recognition or biometric authentication to identify the user. Mobile Identity APIs help prevent fraud, duplicate cards or identity theft and guarantee the user's identity in critical applications in sectors such as healthcare, finance and public administrations, among others. The smart factory: manufacturing, maintenance and logistics. Dario Cesena, CEO of Geprom, Part of Telefónica Tech, participated in this presentation dedicated to connected factories. Solutions based on connectivity technologies, Cloud and Edge Computing, Cyber Security and AI of Things (Internet of Things, Big Data and Artificial Intelligence) allow optimising operational management, digitising systems and processes, making production more efficient and sustainable or collecting, analysing and correlating data, helping to make business decisions in real time. Juanjo González, IoT connectivity product manager at Telefónica Tech AI of Things, participated in 5G IoT Connection: from space to the whole world, a panel dedicated to 5G and LPWA connectivity technologies that are driving the mass adoption of IoT devices. The session delved into our solution developed with SatelIoT that can provide satellite connectivity to IoT devices to provide global coverage, even in remote locations, as a complement to terrestrial communications. In the Aristeo session the industrial God of OT bees, our colleague José Cascallana, manager at Telefónica Tech's C4IN Cybersecurity Centre, demonstrated how Aristeo approaches industrial Cyber Security in a native way, deploying real industrial systems all over the internet as honeypots. In this way, Aristeo contributes to generate intelligence and knowledge that helps to identify and stop threats when they pose a risk to our customers' infrastructures. In the Digitalisation of the mining industry: the success of our customers, our Director of Industry 4.0 and New Business, Andrés Escribano, and Jorge Azaldegui, Head of Sales Specialists, discussed with Klever Morvely, manager at Minera Las Bambas, the growing need in the mining industry to adopt digital solutions that make their operations more efficient and sustainable, that add value to their processes and optimise their results through data, while reducing the human risks associated with mining activity. José Luis Núñez, Global Head for Blockchain & web3 at Telefónica Tech, anticipated in the DeFi-ning Opportunities session the next generation of financial services thanks to decentralised finance (DeFi, powered by Blockchain and web3 technology) that are challenging centralised financial systems for the benefit of people thanks to disruptive, accessible and secure solutions. Javier Zorzano, Head of Technology of Telefónica Tech AI of Things, and Shahbaz Ali, Head of Product of SatelIoT, participated in the 5G IoT Summit: Hybrid NB-IoT and Satellite Solutions. This event was dedicated to 5G connectivity as a key technology for interconnecting and operating billions of IoT devices for countless purposes. At the 5G IoT Summit we heard use cases and success stories that implement these technologies, enabling new business models, making production processes and company operations more efficient, saving time, resources and money, and reducing their environmental impact. The Smart and sustainable agriculture session by Ana Pociña and Paz Revuelta, product manager at Telefónica Tech AI of Things, was dedicated to how new generation digital technologies, such as Smart Agriculture solutions, are essential for the agricultural sector, to address challenges such as water scarcity, rising prices of resources and raw materials, increased demand, climate change or the growing interest of consumers in consuming local, healthy and sustainably produced food. In 5G Revenue monetization business models and platforms for non-linear growth, our colleague Bernardo Campillo, Head of Industry Partnerships at Telefónica Tech AI of Things, addressed how to tackle some of the biggest challenges for adopting cutting-edge digital technologies, such as high investment or the difficulty of demonstrating return on investment in some cases. The Open Gateway initiative, in collaboration with GSMA, aims to align all ecosystem actors to promote collaboration and innovation, and to share risks and benefits. Our new Transformation Handbooks As usual, on the occasion of the MWC we have published two new Transformation Handbooks that explain with use cases and success stories why and how digitalisation is key to the progress and sustainability of our society. You can download them in English, in PDF format, directly from here: Making Progress Happen Making Innovation Happen —You can also freely access and download the Transformation Handbooks from the 2022 edition and 2021 edition. José María Álvarez-Pallete, President of Telefónica and GSMA, presented at Mobile World Congress the GSMA Open Gateway. This initiative brings together more than twenty major operators so that telecommunications companies can share open and standardized APIs with the industry, large technology companies, hyperscalers, aggregators, and service developers. This will provide universal access to 5G networks and telco infrastructures from different operators. In this way, the networks of operators become platforms on which to develop new services and business models, benefiting the entire digital ecosystem, users, and companies. Among the uses and applications of networks as platforms are the automation of industry, autonomous driving, remote surgeries, gaming, emergency management, holographic communications, or virtual and immersive worlds.

Algorithm is a very trendy word, as it relates closely to automation, data-driven decision making, and Artificial Intelligence in the digital realm. Algorithms are used in many machine learning systems and neural networks to perform tasks such as image classification, pattern recognition, or data generation, including content like text, images, or music. An algorithm is a defined series of specific steps to perform a particular task or solve a problem. Nowadays, algorithms are present in many common systems and applications: they determine what posts we see on social media, which route we take with GPS, what news we read, or what suggestions are shown to us on online stores or streaming platforms, to name just a few examples. Al-Juarismi and the origin of algorithms However, algorithms are not a modern phenomenon. Their origins can be traced back to ancient times. They were probably used as early as ancient Babylon in 2500 BC, and continued to be developed in later cultures including Egyptian, Greek, and Indian. One of the most well-known is Euclid's algorithm, developed around the 3rd century BC. More "recently," in the 9th century, the Persian mathematician Al-Juarismi (or al-Khwarizmi) compiled his mathematical works in a compendium that he published around 825 AD, contributing to laying the foundations of algebra and modern mathematics, including the numerical systems we use today. AI OF THINGS How to start programming in Artificial Intelligence: languages, tools and recommendations January 18, 2023 Al-Juarismi's publication included a series of solutions to algebraic problems and described methods for solving linear and quadratic equations (of first and second degree, respectively, essential in programming and problem-solving in science, engineering, and technology) using a set of rules and procedures that we now know as algorithms. On the origin of the term algorithm, the most widely held belief points to the Latinization of the name Al-Juarismi (Algorizmi), which later derived into algorismus, although its exact etymology is not entirely clear. Al-Juarismi was a highly influential author in the Middle Ages due to his contributions to mathematics, astronomy, and geography. In any case, the term 'algorithm' was adopted in medieval Europe to refer to the methods of the Persian mathematician, an author of significant influence for his significant contributions to mathematics, astronomy, and geography. Due to his contributions to modern mathematics, Al-Juarismi can also be considered one of the primordial fathers of computing, as his work in solving problems through algorithms has been fundamental to the development of computer science. Currently, algorithms are essential for programming and the functioning of most computer systems. They are used to solve a wide variety of problems in fields such as Artificial Intelligence, cryptography, computer security, or process optimization, among other uses. Algorithms and Artificial Intelligence In the field we are concerned with, algorithms provide a framework for Artificial Intelligence systems to learn and evolve. Thanks to them, Artificial Intelligence can perform complex tasks such as natural language processing, identifying anomalies and objects in images, generating content, or detecting patterns among large volumes of data and making decisions based on that information. AI OF THINGS Ghosts in the machine: does Artificial Intelligence suffer from hallucinations? February 20, 2023 However, algorithms are not the only thing needed to develop Artificial Intelligence systems. Large amounts of relevant and high-quality data, as well as computer resources with the necessary power and capabilities to process them, are also necessary. In addition, ethics, privacy, transparency, and security are also important aspects to consider when building trustworthy Artificial Intelligence, as its application can have a significant impact on people and society. Featured photo: Charles Deluvio / Unsplash

We have redesigned the Telefónica Tech website to represent who we are as a digital solutions integrator. We also want to share what we do, who is behind it and how next-generation digital technologies are making companies and organisations more efficient, competitive, and resilient. The new Telefónica Tech website focuses on our most valuable assets: The people that make up the Telefónica Tech team in different countries and regions: more than 6,000 professionals who work every day to provide innovative solutions to millions of customers. The technology partners we share two commitments with: to develop the best products and services, and to help customers achieve their goals. Our customers, who we support in their digitalisation process by integrating the solutions they need to grow into their systems and processes. Because their success is our success. Our technologies in connectivity, Cyber Security, Cloud, IoT (Internet of Things), Big Data, Artificial Intelligence and Blockchain... And the innovation and development labs we have in different cities in Europe and America. We also give visibility to analysts in the technology sector who know (and acknowledge!) our capabilities and the value we bring to our clients. “We have improved Telefónica Tech's website to continue positioning ourselves as the best technological partner in the digital transformation for our customers" María Díaz. Head of Marketing & Communications, Telefónica Tech We have also developed a News section that brings together the initiatives, events and multimedia content you need to stay informed about how digital technologies are creating new growth opportunities for companies and society. We would love to hear from you. We invite you to visit the new Telefónica Tech website and join the conversation or share with us any comments that will help us improve. Thank you!

The term Smart City used to refer to "cities of the future", but Smart Cities are increasingly turning the present. Thanks to the use of digital solutions such as IoT (Internet of Things) and Artificial Intelligence, among other technologies, it is now possible to sensor cities. Capturing real-time data from the urban environment —and its infrastructures and services— allows optimising and automating processes and making better management decisions. This makes cities that embrace digitalisation increasingly healthier, more attractive and safer. With more efficient public services and a lower environmental impact. Smart cities are able to grow in a more sustainable way and improve the quality of life of their citizens. We have brought together six key components of today's Smart Cities. They include solutions that enable features today that not so long ago defined the cities of the future: Smart parking Smart mobility solutions make it easier for drivers to find parking spaces in urban areas. This improves traffic flow, reduces emissions, and promotes local commerce and citizen satisfaction. These solutions can also be applied to park-and-ride facilities, airports, hospitals, shopping and leisure centres or natural areas. Smart Transport Many public transport systems are already interconnected, enabling coordination between different modes of transport and allowing them to provide real-time information on their location, time of arrival at the stop, journey time and more. Similarly, smart transport facilitates "mobility mixes", journeys that combine different modes of transport according to the context and individual needs: private car, public transport, shared bicycle or scooter… Smart street lighting City lighting accounts for between 40% and 70% of municipalities' electricity bills. It is possible to reduce costs and emissions, improve energy efficiency and reduce light pollution by integrating IoT devices and connectivity for smart management and remote management. Smart street lighting offers new business opportunities and benefits for both cities and their citizens. Mobility management Mobility control systems for vehicles and pedestrians provide timely information on the status and possible incidents affecting mobility. These systems calculate and even anticipate the most convenient route for public transport, drivers and pedestrians. They also automatically manage traffic lights and other signals to adapt to different contexts and unforeseen events to optimise mobility and reduce congestion. Efficient waste management Technology is already making it possible to improve the management of municipal waste, improving the quality of the service, saving costs and reducing its environmental impact. Not all districts in the same city generate the same type of waste or the same amount of waste. Technology makes it possible to obtain real-time information on the status of the containers. It is possible to combine this information with a vehicle fleet management system to plan optimal collection routes depending on collection needs, areas, volumes, or types of waste. Efficient municipal waste management is essential to improve recycling, promote the circular economy and reduce environmental impact. Monitoring environmental parameters Monitoring environmental parameters makes it possible to assess the quality of the urban environment and reduce environmental, light or noise pollution. Thanks to the deployment of IoT sensors, it is possible to monitor these data in real time in order to know the situation accurately and make better decisions. The monitoring of environmental parameters also makes it possible to measure parameters such as the concentration of CO2 or harmful particles or pollutants. Or meteorological phenomena that can influence the functioning of the city. * * * If you want to know more about the present and future of Smart Cities, visit our new Smart Cities section of the Telefónica Tech website.

Smart street lighting is one of the pillars of smart cities. In fact, it is one of the best examples of what the term Smart City means: the application of next-generation digital technologies to improve the lives of citizens with more efficient and sustainable public services. The concept of smart street lighting brings together all these advantages thanks to the confluence of LED lighting technology, connectivity, IoT (Internet of Things) devices and management platforms with Artificial Intelligence (AI). In this way, each luminaire or streetlight in the public lighting network is connected via 5G or NB-IoT communications networks to send the data captured by different sensors (lighting, environmental or consumption, among others) to a platform capable of automatically optimising the operation and individual efficiency of each luminaire. Why should energy be consumed when there is no one in the street? Smart street lighting not only can adjust the intensity of light depending on the presence of people on the street. It also has the ability to predict, thanks to Artificial Intelligence algorithms, when and with what intensity it will be necessary to switch on each luminaire. Or the lighting of a building or monument, for example. This improves the efficiency of the network and also the feeling of safety and the perception of service for citizens. Smart street lighting has the potential to reduce electricity consumption and pollutant emissions significantly. These savings are in addition to the lower consumption implicit in LED light sources. LED lighting is not only cheaper and more efficient, but also has a significantly longer lifetime than conventional light sources, gas or filament lighting. Savings and new business opportunities for municipalities Smart street lighting allows municipalities, councils and city governments to take advantage of the ubiquity of streetlights to provide additional services, including: Sensors to combat light, noise and environmental pollution. Charging points for electric vehicles. Security and traffic control cameras. Wifi access points to municipal networks. Recharging points for public transport cards. Information or advertising panels. Mobile phone and 5G antennas. Some of the additional services have the potential to generate extra revenue for municipalities. It also means better service and attention to the citizens, fewer calls for warning or complaints about broken luminaires, more efficient maintenance.... And, of course, it increases the attractiveness of the city. Both for citizens and tourists, by promoting social and cultural activities, as well as for businesses and companies. Benefits of Smart urban lighting for citizens A smart street lighting network has a positive impact on citizens and on the image of cities. Adapting the lighting to the needs of the streets, for example, improves the safety of public spaces and the mobility of both people and vehicles. Smart public lighting also reduces light pollution and the nuisance that fixed and constant intensity lighting sometimes causes to nearby premises and dwellings —including flora and fauna— improving the quality of life of citizens. It also benefits citizens by enabling the new services already mentioned, such as charging points for electric vehicles for residents without a garage or domestic charging point. Featured photo: Vlado Paunovic / Unsplash

A few years ago, Google's then CEO Eric Schmidt popularised the concept of “augmented humanity”. This term refers to the ability of technology to "enhance human capabilities" to make us more efficient. To achieve better results with less effort. In short, “'Augmented humanity is about computers helping us with tasks we are not very good at, and us helping computers with tasks they are not very good at." —Eric Schmidt, former Google's CEO In his talk, Schmidt highlighted the potential that Artificial Intelligence was beginning to prove to improve our lives. A technology that Google had already been applying for some time in some services. Artificial Intelligence as a tool and not as a replacement Schmidt then highlighted how Artificial Intelligence —a term first defined in the 1950s by John McCarthy— was beginning to show real progress in automating tasks that were complex, repetitive and monotonous. Even unmanageable for humans. Their adoption would thus allow us to focus on tasks related to "critical thinking and creativity. “Augmented humanity is about embracing AI as a tool to improve people's lives, not as a replacement.” —Eric Schmidt, former Google's CEO But what are those repetitive and monotonous tasks that we can automate with Artificial Intelligence? The following are some examples: Analysis of large amounts of data from multiple sources to extract insights to make better decisions and optimise processes. Pattern recognition in data to automate production, prevent incidents, anticipate future events or identify trends or preferences. Image analysis to extract information from photographs and videos and enable machine vision. Fully or partially autonomous driving and driver assistance systems to reduce the number of accidents and optimise transportation. Robotics to automate physical tasks, machinery and manufacturing, production or logistics processes. Natural language processing to automate communication-related tasks such as customer service and support, translation or content generation. Artificial Intelligence is increasingly present in the digital transformation processes of companies. From rejection to normalisation: the pilgrimage of disruptive technologies In 2010, Schmidt's talk on the growth of Artificial Intelligence generated scepticism and rejection among some people. Even fear. But, as they say, “change is only scary when you are not willing to change with it”. The reasons are numerous, however, and also legitimate. Common fears include job loss, risk to the privacy and intimacy of individuals and their data, lack of regulation, increased inequality and risk of cyber-attacks, ethical considerations to be resolved... Not to mention the fear of artificial superintelligence, a recurring theme in science fiction. Throughout history, even before the industrial revolution, there have been other cases of technologies that have first generated rejection in some people or in society, and then proved their usefulness. A couple of recent examples include mobile phones, because of fears that they could endanger health; or the internet, because it could be used to commit crimes. Both technologies have nevertheless proven their usefulness and are now essential for business and the economy, individuals and society. The landline telephone came to be seen as unnecessary because of the existence of messengers, and raised concerns that other people (the operators) could listen in on conversations. Technology, reskilling and lifelong learning are key in the golden age of AI The arrival of new work tools that arise with "the golden age of Artificial Intelligence", in the words of Satya Nadella, CEO of Microsoft, requires changes. These changes are not only to develop them, but also to incorporate them into work processes, adapt to them and manage them. Just as happened before with computing or the internet. Also, to anticipate a potential gap between demand and the availability of suitable professional profiles. In this sense, "reskilling workers will help to overcome the impact", in the words of José María Álvarez-Pallete, CEO of Telefónica. Training and updating skills is what will make it possible to fill the jobs generated by the digital transformation and capture the new opportunities. “Technology has historically been a net job creator. The introduction of the personal computer in the 1970s and 1980s, for example, created millions of jobs.”—McKinsey Global Institute. For companies, “the winning long-term strategy is to create, cultivate and nurture” technology talent, says José Cerdán, CEO of Telefónica Tech. “It's not about competing to capture talent, but about developing internal recycling and training programmes to strengthen and update skills,” he adds. Achieving this, says Álvarez-Pallete, requires massive retraining through training programmes adapted to new skills. It also requires the promotion of a culture of continuous learning in order to manage the transition to the new digital world in a socially responsible way. Featured photo: Nguyen Dang Hoang Nhu / Unsplash

There is a very close relationship between Big Data and Artificial Intelligence (AI): Big Data is about capturing, processing and analysing large amounts of data. When this data is combined with capabilities such as machine learning and predictive analytics, more value is extracted from that data. This makes it possible, among other things, to find patterns in this data that are "invisible" to the human eye, allowing us to predict and prevent events, offer personalised experiences of use and consumption of products and services, hold care conversations and even create content. Knowing how to program Artificial Intelligence allows you to develop countless solutions and take advantage of the enormous potential offered by Big Data, Artificial Intelligence and Internet of Things. Furthermore, in 2023 the demand for professionals qualified in the development of Artificial Intelligence solutions will continue to grow, because "AI will be present in all the digital transformation processes of companies" in numerous sectors, according to data from Fundación Telefónica's Employment Map. Programming languages for AI development Elena Díaz, head of the Centre of Excellence in the AI of Things product team at Telefónica Tech, is passionate about programming languages focused on exploiting data. As an expert, to program in Artificial Intelligence Elena recommends learning these programming languages: Python is the most widely used programming language for the development of Artificial Intelligence applications. It has many libraries and tools for machine learning, such as TensorFlow, PyBrain or PyTorch, among others. You can start with Python with an experiment for everyone. R is also a programming language widely used for data analysis, data visualisation and machine learning, especially in the field of statistics. SQL is the standard query language for relational databases, widely used in the fields of Big Data and Artificial Intelligence. Knowledge of SQL is essential for the management and analysis of large datasets, essential in the field of Artificial Intelligence. However, as Elena explains, although right now these are the most widely used programming languages in the field of Artificial Intelligence, "we always have to be aware of evolutions and adapt new languages and always be in a continuous learning process". "Once we learn to program, it is relatively easy to switch from one language to another". Elena Díaz, Telefónica Tech. Other languages that also apply to the development of Artificial Intelligence include: Java and C++ are more advanced programming languages and are also used for the development of artificial intelligence applications, including high-performance developments such as neural networks and machine learning algorithms. JavaScript, a very popular language in web development that is increasingly used in the field of Artificial Intelligence, especially for the development of machine learning applications oriented to users accessing them through apps or web browsers, for example. The programming language will depend very much on your specific preferences and needs - it will even depend on your previous programming experience, if you already have some - and also on what you want to achieve or the project you are going to work on. AI of Things 5 free online courses to learn IoT (Internet of Things) in 2023 August 3, 2023 How to develop your Artificial Intelligence skills The first thing you need to do if you are interested in starting programming in Artificial Intelligence is to learn the basics of it. In this sense, it is important to "overcome conceptual, mathematical or technical barriers" and understand basic concepts of artificial intelligence, such as machine learning, computer vision and natural language processing. In addition, you will also find it helpful to: Learn a programming language such as the aforementioned Python, R, Java and C++, which are widely used in the development of artificial intelligence applications. Choose one and dedicate time to learning it. Practice with problems and projects: It is important that you practice with real problems and projects. You can find datasets and problems on websites such as OpenAI or Kaggle. Learn about AI tools and libraries: there are many AI tools and libraries, such as TensorFlow, PyTorch, scikit-learn and Keras. They allow you to build and train AI models easily and you can use them in your projects. Take every opportunity to keep learning: Artificial Intelligence is constantly evolving, so it is important to keep acquiring and updating skills. You can keep up to date with trends, new techniques and technologies through blogs and articles on the subject, webinars, talks and courses (there are many free ones) and by participating in online groups and forums. Elena recommends those interested in Artificial Intelligence to "discover what you like the most and go deeper into it. Specialising in what most motivates you and helps you to continue to grow.” Featured photo: Kelly Sikkema / Unsplash

Digital technologies such as connectivity, Internet of Things or Artificial Intelligence are becoming increasingly common in vehicles. For example, in the form of digital assistants, mobility services, or advanced driving assistance systems. In fact, the automotive industry is one of the main drivers of innovation. The adoption of technology not only improves car manufacturers' products and processes, but also allows brands to differentiate themselves from the competition and attract the interest of drivers by adapting to their needs and improving aspects such as efficiency (reduced fuel consumption and emissions), user experience and safety. Blockchain also has enormous potential as an innovative and useful technology for the industry from the user's point of view. In fact, its adoption in the form of NFT is already beginning to be seen, although for now it is very incipient and almost anecdotal. Blockchain adoption in this area still needs to address challenges such as the infrastructures, regulations and standards that enable its adoption and use. BLOCKCHAIN What was traced first in Blockchain, the chicken or the egg? October 27, 2022 Advantages of using Blockchain for recording vehicle information However, there is little doubt about the advantages and potential of Blockchain technology in the automotive sector, both for manufacturers and the ancillary sector (workshops, parts and spare parts manufacturers, insurers...) and also for users and vehicle owners. Using Blockchain, the information stored and shared benefits from features such as immutability, transparency, and traceability. Therefore, when applied to vehicles, Blockchain technology can be used to record all information relating securely and transparently to the life of the vehicle from the time of its manufacture, including: Date of manufacture, origin, serial number, technical characteristics, configuration, options or body colour, among other data. Maintenance services, including dates, work carried out, parts replaced, modifications, bodywork repairs, recalls or MOTs. Origin of spare parts used and details of replacement elements, to ensure authenticity and prevent the use of second hand or counterfeit parts. Vehicle mileage and battery charge cycles in the case of electric vehicles, to avoid the risk of tampering with the odometer or battery charge cycle counter in buy and sale transactions. Ownership of the vehicle to certify ownership, as well as the registration certificate, reservation of title, payment of taxes, insurance, etc. and to keep a historical record of the owners and uses of the vehicle throughout its life. As we said, the advantages of storing these and other data using Blockchain lie in the fact that this technology improves the security and integrity of the information recorded. Blockchain stores information in encrypted blocks that are stored in different nodes of a network, which means that it is very difficult to change or delete any data without leaving a record. The use of blockchain technology not only backs up vehicle documentation that is susceptible to loss or alteration, such as the maintenance book, but also provides greater transparency in the process of recording information. All of it is also available for auditing and verification. BLOCKCHAIN The 7 priorities of a company when adopting Blockchain October 24, 2022 Blockchain to securely track the status and history of a vehicle In this way, by having access to all this information, anyone can know with greater certainty the condition of a vehicle and its maintenance history, both when selling and buying it. This improves confidence and security in buying and selling transactions by reducing opacity and the risk of fraud. Also based on this information recorded with Blockchain, car workshops have access to a detailed and reliable history of repairs, modifications, maintenance needs or possible incidents with a vehicle. This same information would also allow insurance companies to assess the vehicle in detail and make a more accurate calculation of its condition and value, as well as the services and the most appropriate premium for its owner. Featured image: Popescu Andrei Alexandru / Unsplash

With the digitization of companies and organizations and our increasing reliance on digital technologies, data and information protection must be prioritized. The adoption of cutting-edge digital technologies is not only transforming our lives, economy, society and improving our relationship with the environment: it also means an increase in the number of malicious attacks and the sophistication of cyberattacks. Because as Cybersecurity techniques and technologies improve, so do the tactics and methods used by cybercriminals. This forces companies to increase their resources to protect their data and systems, which are increasingly valuable and critical assets for the operations and continuity of any organization. Data and IT and OT systems are becoming more and more valuable for companies, and are crucial to ensure their continuity and resilience. We have selected a few posts to say goodbye to this year and welcome 2023. Contents that address the different types of attacks and threats, techniques to prevent them and the tools to detect and respond to security incidents. They also refer to the best practices that organizations should apply to protect themselves from threats. Additionally, they emphasize the need for a robust security strategy to protect them from intrusions and attacks. Cyber Security Where is your company on the cybersecurity journey? April 20, 2022 Cyber Security 3 Key Cyber Security Considerations July 3, 2023 CYBER SECURITY The risks of not having controlled exposure to information (I) January 12, 2022 CYBER SECURITY Attention: Data leak! (In search of lost data) November 3, 2022 CYBER SECURITY Human factor key in cyber security September 28, 2022 Cyber Security Attacking login credentials June 22, 2022 CYBER SECURITY XDR, the cybersecurity trend that dominated the RSA Conference 2022 June 15, 2022 Cyber Security 'Insiders' in Cybersecurity: “Catch me if you can” April 25, 2022 CYBER SECURITY Where does ransomware attack? Three main pillars October 5, 2021 CYBER SECURITY XVI STIC Conference: 5 trends in Cyber Security highlighted by our analysts for 2023 December 12, 2022 CYBER SECURITY Digital Identity Wallets against identity theft fraud February 8, 2022 Cyber Security Selecting a managed security service provider (MSSP): 5 key factors to keep in mind October 18, 2022 Cyber Security Cybersecurity in OT: a need with differences December 19, 2022

AI of Things (Artificial Intelligence of Things) is the set of technologies that bring together IoT devices —physical objects with sensors, software and connectivity— with Big Data and Artificial Intelligence solutions that allow processing, analyzing and extracting insights from large volumes of data. Some of these IoT (Internet of Things) objects can range from thermostats and household appliances, vehicles, buildings, or wearables (activity bracelets, watches, medical devices...) to infrastructures, supply networks, machinery, or industrial systems. This way, thanks to the sensorization of the physical world, it is possible to build a data-driven digital version of the environment, allowing us to recognize patterns or predict results, automate tasks, optimize processes, anticipate failures and needs or generate insights that help to make data-driven decisions. The application of AI of Things technologies multiplies the value of connected things and creates new business opportunities. Throughout this year, we have published a number of posts related to the AI of Things technologies that we develop, use and implement at Telefónica Tech: AI of Things Smart football stadiums: the world's greatest show, made even better May 25, 2022 AI of Things AI of Things (VIII): socio-demographic segmentation and video analytics to improve shopping experience July 13, 2022 AI of Things AI of Things for efficient and sustainable water management August 21, 2023 AI of Things Generative Artificial Intelligence, creating music to the rhythm of perceptron July 18, 2023 AI of Things How IoT solutions help us deal with rising energy prices? August 24, 2022 AI OF THINGS Can Artificial Intelligence understand emotions? May 23, 2023 AI OF THINGS AI of Things (X) 10-minute delivery: how Artificial Intelligence optimises delivery routes September 29, 2022 AI of Things Endless worlds, realistic worlds: procedural generation and artificial intelligence in video games August 22, 2022 AI OF THINGS Big Data and Artificial Intelligence solutions for the tourism industry September 27, 2022

IoT (Internet of Things) is one of the fundamental technologies in more and more digital transformation processes and for the development of new business opportunities. It consists of the use of connected devices and sensors that generate or capture data through common objects such as water and electricity meters, sports and wearable clothing, vehicles, industrial systems, home automation sensors, etc. This large network of connected IoT devices generates a huge amount of data from the physical environment. This data is captured and can be processed with technologies such as Cloud, Big Data and Artificial Intelligence to help make data-driven decisions that will in turn have an impact on the physical environment and people. A simple example would be the case of a smart HVAC system that takes into account data from different sensors (thermostats, sunlight intensity, occupancy and circulation of people, etc.) to calculate and adjust the optimal temperature in a commercial space IoT devices can create virtual copies (digital twins) of physical infrastructures, facilities, factories or services and environments that accurately recreate their state, operations, and behaviour. It is important, therefore, as with Artificial Intelligence, to ensure that the data captured by IoT sensors and devices is recorded, stored and used in an ethical and responsible manner. Particularly when personal data is involved; as in the case, for example, of a smartwatch capable of measuring physical activity, sleep and other health-related parameters. Three ingredients for an "ethical IoT" Public trust, as with all technologies in general, and digital technologies in particular, is essential to drive mass adoption to harness the power and potential of IoT to improve the environment, the economy and society. Transparency: As an essential element of trust, manufacturers and companies must be honest and clear about what data they will capture, how it will be used, for what purpose, and how it will influence decision-making. By knowing this, users also understand how their data will be used and can make an informed decision. Accountability: Companies make a commitment by receiving user consent that makes it necessary to ensure that data are captured, stored, and processed in a responsible manner. Especially when personal information is involved, data should be kept confidential and secure and always processed for the benefit of the user, not just for financial return. Security: a company must ensure that in order to keep data private and confidential the information captured by IoT sensors and devices, companies must ensure that they set up an ecosystem that protects the user and their information. This includes ensuring that both IoT devices and data are not exposed to cyber threats and malicious attacks, and that any data is only used for the intended purpose and always with the user's consent. AI of Things AI of Things for efficient and sustainable water management August 21, 2023 Initiatives promoting an ethical Internet of Things Ethics is essential for any company developing, implementing or making use of IoT devices. Ensuring that data is protected and that it is captured and used in an honest and transparent way, always with the knowledge and consent of users, allows companies to respect people's digital rights and develop a trusting relationship with the public. There are a number of international initiatives, both public and private, that guide and participate in the development of ethical IoT technologies, including the European Internet of Things policy, The IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems or The Centre for Cybersecurity del World Economic Forum. Many large companies and big-tech are also demonstrating their efforts and commitment to protecting people's digital rights and implementing the principles of ethics and transparency required by the massive use of data generated by sensors and IoT devices, and their convergence with Big Data and Artificial Intelligence. Many large companies and technology companies are demonstrating their efforts and commitment to protecting people's digital rights In this regard, New America's Open Technology Institute's Ranking Digital Rights (RDR) initiative ranks the leading telecommunications, internet, and mobile ecosystem companies whose decisions collectively affect billions of people around the world. RDR annually compiles the Corporate Accountability Index which, in 2022 and for the third consecutive year, leads Telefónica for, among other categories, having "clear and robust policies regarding the collection and use of data" and for being the only company among those analysed with a commitment to respect human rights in the use of Artificial Intelligence.

LPWA and 5G networks enable the interconnection of millions of objects and IoT (Internet of Things) devices such as connected sensors to send captured or generated data to Cloud platforms where this data is managed and processed. Thanks to these networks, IoT technology offers new business opportunities in multiple sectors or enables efficient management of resources such as water or energy, among other use cases. What is LPWA connectivity Low-Power Wide-Area (LPWA) networks and 5G connectivity are key to the mass adoption of IoT solutions. Both connectivities are complementary and enable the mass use of connected IoT devices when thousands of them concur in a limited area, such as in a smart building or connected factory, and up to millions of IoT devices in the same geographical area, such as a city. LPWA connectivity stands out for: Low power consumption, which guarantees the autonomy of IoT devices for as long as 10 years or more even when running on batteries. Long range, allowing sensors and actuators to be installed in remote locations or difficult to access terrain, such as crops in rural areas. LPWA also has a high penetration capability in case of physical obstacles, both indoors (such as basements or garages) and outdoors. Another key aspect is that the cost of the hardware required to connect IoT devices to LPWA is relatively low, which makes it cheaper and simpler to deploy and provides an additional driver for mass adoption of IoT solutions. An important difference between LPWA and 5G is that LPWA, unlike 5G, is not designed to transmit large amounts of data, such as that needed to make a voice call or stream video. In contrast, LPWA is very efficient and gives connected devices the ability to send small data sessions for years; such as measurements of water consumption, soil moisture or temperature or gas pressure, to name a few examples. Therefore, as we say, LPWA and 5G are complementary connections and both play a key role in the mass adoption of IoT. AI of Things Satellites with 5G technology to provide IoT coverage worldwide April 10, 2023 NB-IoT, the LPWA and 5G connectivity from Telefónica Tech Telefónica Tech is committed to providing IoT technology with robust, secure, and efficient connectivity through two communications technologies that fall under the umbrella of LPWA and 5G communications: NB-IoT (Narrow Band-IoT) for mass deployment of sensors, meters or IoT telemetry. LTE-M (LTE for Machines) for uses requiring mobility, such as fleet management. Both connections support 5G and LTE and benefit from features such as end-to-end security and authentication offered by LTE, among other advantages.

Internet of Things devices and sensors enable the sensorisation of the environment, the fusion between the real world and the digital world. Thanks to IoT, smart devices generate a large amount of data that can be captured and processed with technologies such as Cloud, Big Data and Artificial Intelligence, allowing better decisions to be made and connected objects to act automatically and accurately, without the need for human intervention. The development of technology has always revolutionised the business sector in one way or another. In the case of the Internet of Things, its use in the internal organisational aspect of companies can be a revolution when it comes to optimising work, production or processes. The connectivity provided using IoT devices linked to Cloud platforms makes it possible to create new business models, products and services, and market strategies. In the business world, this also brings benefits such as optimising the use of assets, improving the customer experience, saving on operating costs and creating jobs IoT devices generate a wealth of information that can be captured and processed with technologies such as Cloud, Big Data and Artificial Intelligence, helping to make data-driven decisions. On the one hand, this technology allows companies to know what their weaknesses and strengths are, as they know their customers' activity and even their interests, due to the data provided by this type of device. The advantage of this is that the company can adapt the products or services offered to the specific needs of each customer. In addition, it also makes it possible to analyse the strengths and weaknesses of the employee in order to make the most intelligent decisions and distribute the work in the most efficient way. The remote monitoring provided by IoT reduces operating costs by automating internal and external processes. It also enables the redeployment of available resources in a way that is more consistent with business objectives. AI of Things Smart football stadiums: the world's greatest show, made even better May 25, 2022 Examples of IoT technology in industrial and business environments IoT technology, in combination with technologies such as Big Data and Artificial Intelligence, depending on the needs and characteristics of each organisation, is already being used successfully in different market sectors, such as: Logistics: The installation of a connected device in a company's distribution vehicles provides real-time information on the use and status of the vehicle and its precise location at all times thanks to the GPS system. This enables the optimisation and protection of personnel, vehicles and cargo and the optimisation of delivery routes. The logistics of the companies are also improved, as the coordination with distributors and suppliers’ benefits. Agri-food: The use of connected IoT sensors and actuators in the agriculture and livestock sectors enables improved productivity, efficiency and decision-making processes based on data captured by sensors and machinery that make up the value chain to form smart agriculture. The data collected will allow production models to be updated more frequently, shortening planning and improvement cycles, while historical data will allow trends, patterns and opportunities for improvement to be understood with lessons learned and combined with information captured by moisture sensors, soil, satellite and drone imagery Tourism: it allows both public and private entities to have a complete view of the anonymised behaviour of tourists, allowing them to anticipate their needs and adapt to their demands and preferences, as well as to provide and improve the tourism offer. Healthcare: there are major challenges facing the healthcare sector, in particular the ageing population and demographic growth, which make it necessary to seek efficiency in the delivery of healthcare services, while maintaining economic sustainability and offering a better patient experience. Industrial: IoT sensors can capture information from any process and turn it into value through the application of Big Data and Artificial Intelligence. LPWA and 5G Narrow Band (NB-IoT) wireless connectivity enables wireless and connected factories, improving employee productivity and safety, savings and efficiencies from IoT sensor data analytics, predictive maintenance for rapid response and planning, augmented reality environments and digital twins. Energy and utilities: IoT enables smart management of essential resources such as water, energy and gas, as well as technical infrastructures for greater operational efficiency and reliability of a large part of their processes, which in turn allows for a reduction in environmental impact and the development of new business models. Retail: to ensure a better, personalised and homogeneous shopping experience across all channels and to differentiate from the competition. Some of the main trends in the sector include localisation and hyper-personalisation in the shopping experience, the improvement of the physical shop experience and commercial spaces, the transformation of certain locations or points of sale into distribution centres and home delivery service to satisfy online sales. A good example of what IoT can offer to make business environments more efficient and productive. The big challenge facing companies that implement IoT technology is the control and management of this type of technology, employees must be trained to know the functions of these new devices in order to make the most of them and ensure that there are no errors in their use. In this way, the installation of this technology also means the creation of new jobs. In fact, new courses and master's degrees specialising in the operation of IoT are gradually being established. All this without losing sight of the main objective: to facilitate the daily lives of the people involved in the different processes. After all, the human being is at the heart of digitalisation and IoT transformation.

A few days ago, we held the meetup "The defensive line in Cyber Security", a face-to-face event that we organised at the Ironhack space in Matadero Madrid, through Telefónica Tech's Trending Techies initiative. The meetups around the Cyber Security Techies and Data Techies communities generate conversation and networking spaces in a relaxed atmosphere (and some snacks) between professionals, students, companies, and the public interested in new generation digital technologies such as IoT, Cloud, Big Data, Artificial Intelligence, Blockchain and Cyber Security. On this occasion, the meeting was dedicated to the role of the Blue team as the first line of defence before, during and after a cyber security incident occurs. The master of ceremonies for the event was Martiniano "Marty" Mallavibarrena, Global head of incident response at Telefónica Tech. Or, for that matter, our "SWAT chief" when it comes to intervening quickly in a cyber security incident. During the meeting, the speakers shared their professional experience and knowledge through three different cases that brought together the technologies, roles, techniques, and professions involved in detecting, preventing and recovering from a cyber-attack. Intelligence (human and artificial) against cyberthreats Álvaro García-Recuero, senior researcher at the Barcelona Supercomputing Center (BSC), spoke about federated learning as an alternative for training AI models in a secure, private, and robust way. In his case applied to a project for the classification of sensitive content on the internet that is able to learn and protect itself from malicious attacks or user errors. Álvaro explained how this type of technology can also be applied to cyber security, for example, to detect or prevent cyber-attacks. And he addressed the need to use Artificial Intelligence in a "responsible and ethical" way, and to take advantage of the capacity of machine learning to protect us from cyber threats. Artificial Intelligence can also be applied in cyber security, both to attack and to defend Of course, assuming that these techniques and technologies are also used by "the bad guys", so their attack tools are getting "better and better at doing evil", in Marty's words. Silvia Hernández, Threat hunter at Telefónica Tech, dedicated her talk "Studying threats to defend ourselves against them" to talk about an intrusion related to Conti and some malicious artefacts to explain how human analytics combined with machine learning and EDR-type systems make it possible to extract information, analyse, block, and respond to threats and complex attacks, as in the case of ransomware attacks to hijack data. The figure of the threat hunter, although a relatively recent role, has become a figure without which “today's cyber security would be totally chaotic”. Cyber Security Policy for SMEs And lastly, Eugenio Martín, risk advisor at Jori&Tech, focused his presentation on preventive cyber security for small and medium-sized companies. He focused more specifically on the cases of educational centres and start-ups, two examples of organisations that are highly exposed and vulnerable because they have a very large "attack surface" (as happens when hundreds of devices and young people are combined in a school) and because of their lower technical and financial capacity to protect themselves and deal with a cyber-attack and its consequences. “We are witnessing ransomware attacks that in just three days, over a weekend, are capable of completely hijacking complex computer systems of all kinds of organisations, educational institutions and businesses." Eugenio presented the 'cyber insurance policy' or cyber security policy for SMEs and organisations. A resource that is still little known but essential, especially for small and medium-sized companies that, in general, are less prepared for common cyber-attacks such as ransomware, phishing or theft of credentials and information. The cyber policy focuses on both prevention (audit, implementation of basic resources, ...) and solution (coverage, risk management, incident intervention...) when all else fails. The problem is that cybercriminals also make use of these technologies, knowledge, and intelligence to increase the "firepower of their attacks" which, correctly applied, can be "impossible to stop", Marty explained, when there are no active cyber security measures in place.

The 21st of October is World Energy Saving Day. During the last ten years, this day has raised awareness of the impact that energy consumption has on the environment and natural resources, to enable more efficient use of energy and offer "universal access" to "affordable, reliable and modern" energy. Energy is one of the pillars of any civilization. There is a relationship between energy and progress. In fact, the Kardashev scale measures the degree of technological evolution of a civilization based on the amount of energy it uses. Or rather, based on its ability to harness the energy resources at its disposal, both on and off Earth. According to the latest calculation, humanity is a 0.7 type civilization on the Kardeshev scale. That means that we can still make much more effective use of the power in our environment. Energy efficiency to accelerate progress and sustainability However, while energy consumption implies progress, its use also requires the use of limited natural resources. This means that it is usually harnessed at a high economic, social, and environmental cost. This trade-off can be solved by promoting energy efficiency: using as little energy as possible to get the intended result. Energy efficiency reduces environmental impact and carbon footprint, while boosting "economic growth, human development and environmental sustainability", says the World Energy Forum. Photo: Erik Dungan / Unsplash Digitalization for efficient use of energy resources Digitalization is one of the levers at our disposal to increase energy efficiency. The convergence of technologies such as the Internet of Things (IoT), Big Data, and Artificial Intelligence, among others, makes it possible to better manage energy from production to consumption, for example: Improving the management of energy and natural resources such as water, gas, or electricity, achieving enhanced operational efficiency and process reliability. Added an additional layer of intelligence to infrastructures also allows for the proper distribution and use of these resources, and reduces losses. Optimizing energy production with conventional and clean energy sources (such as wind and solar) by incorporating sensors and smart hardware at different stages of production. Also, by applying predictive production systems and solutions for the integration of distributed energy resources, among other possibilities. Reducing energy consumption in homes, public and commercial spaces and businesses by sensing the environment, taking into account the context and learning from user habits. Monitoring energy consumption enables the implementation of data-driven energy saving strategies and the design of accurate and customized savings plans. AI of Things AI of Things for efficient and sustainable water management August 21, 2023 Technological advances that improve efficiency and sustainability in digitization Digital solutions of this type can improve energy efficiency at different levels of energy resource management. Telefónica Tech also develops most of these solutions using ultra-efficient technologies with a lower resource consumption that reduces its environmental footprint. Thus, the products and services in our portfolio are designed to reduce their impact to promote green digitization in any type of sector, field, and activity.

Before tackling the digitalisation of their organic cherry orchard, the Vicente brothers, the caretakers of the Frutas Mifra cherry farm, had to ride around the entire farm on a quad bike to open, close, check for leaks and supervise all the irrigation valves. Almost 40 valves in total had to be opened and closed by hand, one by one, then monitored to keep track of the amount of water reaching each tree. A laborious task that required time, effort and energy: Frutas Mifra's cherry orchard, located in the region of Codos, Zaragoza, is extensive, with a significant slope and has areas of difficult access that complicate the care of the fruit. Now all this process is carried out remotely, from the farm's office or from the mobile phone. This enables them to know at all times and attend to the changing needs detected by the connected sensors from anywhere, "even while you are doing other business, attending to personal matters or working on other tasks in the field", the Vicente brothers explain in the following video: Connecting farmers to data This remote management is possible thanks to the use of IoT sensors and actuators and 5G Narrow Band connectivity (NB-IoT networks) to condiv a smart irrigation system that allows accurate control of the amount of water reaching each cherry tree, which is key to determining the taste of the fruit. Smart irrigation also detects over- or under-watering due to terrain, soil condition, weather or due to leaks and losses. Frutas Mifra uses the technological solution resulting from the partnership between Spherag and Telefónica Tech to have a better knowledge of what is happening on its farm. Thanks to this knowledge, each cherry tree can be supplied with the water it needs to achieve a harvest of organic cherries with the quality and quantity demanded by customers in Abu Dhabi, Germany, Spain and France. Organic cherry growing requires attention, time and resources. Each tree is exposed to external factors that are difficult to predict, such as weather, and needs careful care day and night, every day. This is particularly important during the months between blossoming and the delicate period of fruit set until harvesting. This is the only way to achieve a bountiful harvest of perfect cherries. Going digital for a more efficient, sustainable and competitive agriculture Agriculture is a strategic sector exposed to numerous challenges: population growth, scarcity of water and generational replacement, rising costs of energy and fertilisers, nutrients or pesticides, loss of competitiveness, ... On top of this, there is the growing impact of the loss of arable land and weather anomalies resulting from climate change. According to Ecologistas en Acción, agriculture contributes up to a third of the total greenhouse gas emissions - between direct and indirect emissions - to the process of climate change. According to FAO, agriculture will need to produce almost 50% more food, fibre and biofuels than in 2012 to meet global demand by 2050 How digitisation is helping the agricultural sector to become more resilient and adapt to climate change For all these reasons, agriculture urgently needs to address its digital transformation process in order to: Increase productivity and shorten crop cycles to meet demand, save costs and be more competitive. Make efficient use of scarce resources such as water and reduce the use of fertilisers and pesticides to make crops more sustainable and environmentally friendly. Save energy and fuel in the production, supply and logistics chain to reduce costs and greenhouse gas emissions. According to CaixaBank Research, the agricultural sector in Spain uses more than 82% of water usage In this sense, new generation digitalisation technologies such as IoT (Internet of Things) devices and sensors, drones, 5G connectivity or Big Data and Artificial Intelligence, among others, already make smart and precision agriculture possible in most of the crop cycle. The overall use of these technologies already makes it possible to: Have a better understanding of the state of crops thanks to Artificial Intelligence and the combined use of data captured by IoT sensors and other sources of information, such as weather forecasts or aerial, satellite or drone images to anticipate and know what is always happening in the field. Incorporate useful and valuable data in decision-making and have powerful agronomic management tools to prevent pests or diseases in the crop and reduce the use of pesticides, fertilisers and water by applying resources precisely and selectively. Act with agility and adapt production processes to better manage economic, material, human and environmental resources, to increase yield and operational efficiency and to react to unforeseen events and sudden changes in the environment. Photo: Mae Mu / Unsplash

Telefónica Tech is constantly growing and working to be the technological partner of companies in their digital transformation process. As part of this purpose, Telefónica Tech Cyber Security & Cloud launches its new website. A space that we have entirely developed and designed in house, which allows us to promote and share our entire value proposition with our customers better than ever: Our portfolio of Cloud solutions, Cybersecurity, Workplace of the Future, Cloud and Secure Connectivity, and Your 360° Digitalisation. The potential of our Professional Services capabilities, Managed Services and Consulting proposition. Our differential value and the reason why we are the best technology partner for the companies that want to accelerate their digitalisation. Telefónica Tech's Cyber Security & Cloud business unit drives the digital transformation of companies, public administrations and organisations by applying the capabilities of the most advanced Cloud technologies so that they can reach their maximum potential. Always reducing the associated risks thanks to professional services managed by our team of certified experts. The new website represents who we are as digital solution providers and reinforces our position as a benchmark in the market The new Telefónica Tech Cyber Security & Cloud website brings together more than 140 solutions and products that, together with our partner ecosystem, we offer to our B2B customers in the business sectors in which we specialise, such as banking, industry, education and healthcare, among others. Learn how our digital solutions drive business in the real world The new Telefónica Tech Cyber Security & Cloud website, in collaboration with our customers, provides audiovisual resources, whitepapers, infographics and testimonials on some of the case studies that show how our technologies can contribute to the digital transformation of businesses, companies and organisations of any size and sector. Recent examples include: La Marina de Valencia, the 4.0 port that continues to advance in its digital transformation by applying IDoT - technologies related to Cybersecurity, Cloud Computing, certification and 5G connectivity - and which already has intelligent points of light and water supply to reduce its water and environmental footprint. Thanks to 5G technology and Edge Computing combined with Virtual Reality, IE University students can connect remotely and interact with professors and peers in an immersive and enjoyable virtual space that enhances their performance and enables innovative learning resources. Find out why Telefónica Tech is a benchmark in knowledge technologies Based on our numerous research, development, analysis and dissemination projects, the innovation area and cybersecurity laboratory make Telefónica Tech Cyber Security & Cloud an international benchmark in solutions that offer companies a reliable, secure and resilient digital transformation. Our new website makes it easier for users to navigate and helps them find what they need. We have gathered all the information about our innovation centres, patents, technologies... We have also created a lot of content about Cybersecurity and Cloud technologies and all the initiatives we are carrying out to share our knowledge with industries, start-ups, students and universities. Come and visit us at https://cybersecuritycloud.telefonicatech.com/en. We'd love to hear from you and get feedback to help us improve —thank you!

The UN has been celebrating World Environment Day on 5 June every year for 50 years. It is an initiative that seeks to raise awareness among the world's population of the need to respect, care and protect nature. For this year's edition, the United Nations Environment Programme (UNEP) has revived the slogan "One Earth". It is the same slogan it used for the first edition, in 1972, and it is a message that in 2022 is more powerful than ever: it invites us to live sustainably and reminds us that this planet is our only home and that we are responsible for safeguarding its resources. In this context, the technologies that underpin the digital transformation of companies —connectivity, the Internet of Things (IoT), Big Data and Artificial Intelligence, etc.— have proven their potential as a lever for change and their ability to resolve many of the environmental challenges we face. Among other examples, They allow us to improve the efficiency and sustainability of production processes, reduce energy and water consumption and reduce emissions of polluting and greenhouse gases, such as CO2. They help us to improve the management of natural resources and waste, to optimise transport logistics and mobility, to promote renewable energies and to encourage teleworking and the circular economy. However, these same challenges also force us to analyse the environmental impact of adopting these technologies in our businesses and processes, and to identify possible improvements to achieve a green digital transformation with a genuine positive impact on our environment and society. Technologies such as 5G, Internet of Things (IoT), Big Data and Artificial Intelligence or Blockchain, among others, can help reduce CO2 emissions by 15% by 2030. Source: European Commission, Sustainable technologies for (real) green digitalisation With the aim of developing technologies that promote green digitisation, most of the technological solutions offered by Telefónica Tech for the digital transformation of companies generate direct, significant and measurable environmental benefits for our customers or for the customer's users. These products are identified by the Eco Smart seal, certified by AENOR, an independent entity. This is a distinctive sign that visually shows, with an icon and a colour code, whether the product or service is associated with: Energy savings Water consumption reduction CO2 emission reduction Circular economy promotion Therefore, customers of Telefónica Tech products and services with the Eco Smart seal generate significant environmental benefits in their production process or daily activity, and also obtain a financial return from the digital transformation by developing their business in a more efficient and sustainable way. How Eco Smart solutions help the environment Eco Smart services are already being used by companies of different sizes in key sectors - such as tourism, industry, logistics and distribution, retail and banking - to reduce resource consumption and CO2 emissions. Here are some examples of technological solutions that bring direct, significant and quantifiable environmental benefits: Smart corporate spaces and workplace and teleworking solutions for companies and public administrations that reduce commuting: workplace digitalisation avoids millions of tonnes of CO2 emissions. The sensorisation of a building with IoT devices that take into account the context and the environment (occupancy of people, weather conditions, date and time...) to reduce lighting and air conditioning consumption. Smart and connected meters, reduces leakage and water losses in the public network, in irrigation communities or in households. A medical remote care service that saves patients from having to travel to the medical centre. It saves fuel (energy) and reduces pollutant and greenhouse emissions. Monitoring and predictive maintenance, in order to know the state of equipment at all times, makes it possible to anticipate incidents and predict machinery repairs, extending its useful life and contributing to the circular economy. Our customers avoided more than 8.7 million tonnes of CO₂ with Eco Smart solutions last year Solutions for aligning financial, social and environmental sustainability It is essential for companies and public administrations to opt for digital transformation solutions that have a certified environmental benefit, such as the Eco Smart label, to ensure their financial resilience and sustainability and to reduce their environmental impact. It is also to set an example by achieving your ESG goals such as decarbonisation, emission reductions or meeting the United Nations Sustainable Development Goals (SDGs) agreed for your sector. Our Eco Smart solutions saved our customers 8.7 million tonnes of CO2 emissions in 2021, equivalent to planting 158 million trees. Our goal is to avoid 12 million tonnes of CO₂ emissions by 2025. One thing that remains unchanged is our purpose: that the Eco Smart technologies that underpin the digital transformation bring our customers an economic benefit that is aligned with social and environmental sustainability. Featured impage: Photo: Mert Guller / Unsplash

Stadiums are where the magic of football happens. They are the meeting place where fans and rivals experience the thrill of competition. Passion and joy, and also sorrow, are shared in the stadiums with the players and the team, with thousands of fans and even with millions in front of a television. That is why it is always exciting to go to a stadium to watch a football match. An experience that technology, applied to the digitalisation of stadiums (smart stadiums) has the capacity to turn into a memorable experience, increasing the attractiveness of sports venues for fans, viewers and sponsors. Innovative technologies such as 5G connectivity, the Cloud, Big Data and Artificial Intelligence, and the Internet of Things (IoT) offer football clubs everything they need to improve and extend their relationship with their fans, to attract new audiences and to increase the number of spectators in their stadiums. It also allows clubs to be more agile in responding to the demands of fans and advertisers; and to adapt to new football consumption habits, especially among young people. Technology to engage viewers and attract sponsors The digitalisation of stadiums and sports facilities allows clubs to provide services and entertainment ecosystems to attendees. It also enables new dynamic and proximity marketing actions to increase audience participation and loyalty at events or at the club itself. For example, Wifi or 5G connectivity inside the stadium makes it possible for spectators to connect with their mobile phone via the club's app to access exclusive content in high definition and in real time: camera views and additional shots without delay, on-demand replays, interactive content and even live and 360° virtual reality, or overlaying statistical and player performance data. Artificial Intelligence can automate sports broadcasts, enabling clubs to offer spectators a personalised mobile experience, giving them the ability to choose what they want to watch and what they want to share so that they don't miss out on what is happening inside and outside the stadium. This combination of high-speed connectivity and AI also enables new advertising media and formats to capture the attention of spectators and get a better economic return from sports facilities and communication channels, and to expand the sponsorship portfolio. Photo: Thomas Serer / Unsplash Digitalisation also makes it possible to offer 360° video scoreboards and turn stadiums into visual and acoustic spectacle generators in tune with the development of the match and the emotions of the crowd. Both during football matches and at events of all kinds, such as meetings, cultural events or concerts. Sensing the environment to connect with the crowd The use of IoT sensing and Artificial Intelligence also allows clubs to know in detail the behaviour and profile of those attending the course and its surroundings. In this way, clubs obtain insights about tourists or visitors to take into consideration when making operational, strategic or business decisions. For example, to decide what is the best date and time to hold a specific event or launch a promotion, and what type of promotion. Also to know with which public, at what times or in which areas of the stadium different commercial actions work best; or to optimise access control and the flow of attendees, improving their safety and that of the stadium. Sensorisation also increases the operational efficiency of sports facilities when combined with high-speed, delay-free connectivity (5G) and Cloud and Edge Computing technologies. Autonomous and automatic coverage of matches in smart football stadiums This combination of technologies enables autonomous and automated coverage of sporting events. Connected remote cameras and artificial intelligence algorithms are capable of performing real-time game analysis, tagging plays and orienting and switching cameras to produce a signal suitable for live broadcasting -on television, social networks, digital platforms...- that, in addition to: It facilitates the reporting and broadcasting of events, and even eliminates the need to deploy mobile TV units, streamlining operations and reducing broadcast costs while improving efficiency and sustainability. Managed broadcasting from the Cloud platform allows recording and broadcasting to be carried out from multiple locations and in near real-time, thanks to high-speed data transfer. Through the Cloud, production can be done from anywhere in the world, with the best specialists and the best resources. This means an improved experience for the viewer, providing them with a greater number of viewing options, shots and effects to enrich broadcasts and make them more personal. Cloud platform stores a historical audiovisual archive that remains available and easily accessible for the club, the media and the fans, erasing the limits to the capacity to store and manage all the content generated by the smart stadium. The possibilities offered by digitalisation are many, both for football clubs, their fans and spectators. Also for football: the digitalisation of football stadiums turns the world's greatest spectacle into a memorable experience.

Generating photorealistic images from naturally expressed concepts such as "an astronaut riding a horse" or "a bowl of soup that looks like a monster". Or anything else you can imagine, no matter how surreal. That's what Dall-E 2 does, the latest evolution of the artificial intelligence (AI) system announced by research and development company OpenAI, with Elon Musk among its founders. It's true that we've seen similar apps and AI systems before, which generate images from text or keywords. However, Dall-E's latest demo generates images that leave no one indifferent due to their quality and realism, as well as their dreamlike and surreal style. The name Dall-E combines the names of the Pixar character Wall-E and Salvador Dalí, the master of surrealism. The tool is available to the public through registration, but its results can be seen on the OpenAI website and on Instagram. Some images generated by OpenAI's AI model Dall-E The company has shared examples of the images Dall-E produces when concepts, features and styles are combined into a short phrase. Thus the phrase "a bowl of soup that looks like a monster made of play dough" would result in this image and its variants. "A bowl of soup that looks like a monster made of play dough" according with Dall-E. Image: OpenAI Whereas "a bowl of soup that looks like a monster woven out of wool" would result in this other image - and its variants. "A bowl of soup that looks like a monster woven out of wool". Image: OpenAI Different combinations can be tested on the OpenAI website, and this video shows other examples and explains a bit more about what Dall-E is and how it works. Dall-E's neural network “has learned the relationship between images and the texts that describe them,” the researchers explain. “It not only understands individual objects such as a horse or an astronaut,” they say, but has also learned “how objects and actions relate to each other". This is how Dall-E 'knows' how it should realistically represent an astronaut riding a horse. Image generated by Dall-E artificial inteligence when you ask for an astronaut riding a horse. Image: OpenAI To generate the image Dall-E uses a process called “diffusion” which starts by rearranging random patterns of dots and modifying them until the desired result is obtained, producing “images that have not existed before”. Dall-E is an example “of how human imagination and systems can work together to create new things, amplifying our creative potential” Dall-E aims to be an example of “useful and secure” AI According to the researchers, the development of Dall-E fulfils three essential premises for the development of a “useful and secure” AI: It allows the audience to express themselves in a way that was not possible before. It reveals whether the AI system “understands” what is asked of it in writing, or whether it just repeats what it has learned. Helps to understand how the AI system sees and understands the world. Compared to the first version of Dall-E, announced just over a year ago, Dall-E 2 adds new features, as well as increasing the comprehensibility and the quality and complexity of the images and the speed at which they are generated. Start from an existing image and create complex variations, such as changing the angle of a portrait and its style. Edit an existing image to replace one object with another, to add an object that does not exist in the original image, considering styling, shadows, reflections and textures. You can even change the meaning of the image. However, limitations in the use of Dall-E lead to bias In addition to limiting its availability --the tool will be available to a small group of people, mainly AI researchers and some non-commercial artists-- OpenIA has implemented some restrictions on the use of its new artificial intelligence model. These restrictions are intended to avoid harmful or offensive use of the tool by preventing it from generating violent, sexual or politically charged images. It also prevents the generation of images that include known or recognisable people. Avoiding bias and stereotyping is one of the great challenges for artificial intelligence These limitations can, however, encourage bias in AI models such as Dall-E. OpenIA researchers found that removing sexual content to prevent Dall-E from producing adult images causes Dall-E to generate fewer images of women overall. This is not a good thing, reports the publication Vox, “because it makes women invisible." But this is not a problem unique to Dall-E: avoiding bias and the persistence of stereotypes is now one of the biggest challenges “for the entire AI developer community.”

Online dating platforms such as Tinder, Happn and Hinge are seeing exponential growth, slowly sliding on to the home screens of smartphone users all over the world. Last week at the Web Summit in Lisbon, Tinder's CEO, Sean Rad, presented about just how popular the world of swiping and superliking has become, declaring that 80% of people on the app are actually searching for "serious relationships". He also shared that 85% of users are Millennials and that 1.4 billion swipes take place every day, creating 26 million daily matches. Figure 1: Could Artificial Intelligence be a game changed in the world of online dating? However, the massive popularity of turning to online forums to meet potential suitors can cause great frustration for many. In a world where we can digitalise and automate so much of we do, some find it to be too time-consuming, whilst some just get bored of the generic icebreaker conversations. So, what if Artificial Intelligence could relieve online daters of the daily monotony of searching for the perfect match? What if they could invest that extra hour in cooking their favourite recipe or hitting the gym ahead of any potential date? Well, with Bernie, they can. Figure 2: An overview of Bernie's functionalities in the online dating world. Bernie, otherwise know as "Personal Dating Assistant AI", is a startup based out of Vancouver and aims to take the friction out of online dating. This bot lets you write customizable messages introducing yourself to potential candidates, " sounding like you, not someone else". He also provides " freedom from hours of daily swiping", saving users time by eliminating dates who won't work out. Furthermore, he also learns who you find attractive " working hard to meet your standards." The solution relies on both Artificial Intelligence and Deep Learning and the founder reported their number crunching in this blog post, revealing that out of a sample size of 164,519 efforts (actions or events by Bernie), users only reverse Bernie 225 times, giving them a remarkable feedback accuracy of 99.86%. However, whilst Bernie may entertain the serial online dater, how will the potential "victims" feel when they find out it was a robot and algorithms who actually discovered their "unique" profile on online dating platforms? Well, the founder claims that his countless hours of research, experimentation and bug-fixing have been worth it as he has now found a girlfriend - who did not see any problem with his data-driven approaching to dating. On a more negative note, Tinder is also suffering from an invasion of trained Artificially Intelligent chatbots trying to trick users. Candid Wueest from Symantec explained that " the reason they exist is because somebody, somewhere is making money out of them" in an article in El Confidencial. These bots do this by driving traffic to commercial websites where they try to get users to suscribe to premium services, sharing their credit card details which can be used by potential fraudsters - all in their innocent pursuit to find love. An example of this was highlighted in TechCrunch, where many users reported fake profiles of women who were driving male users to a mobile game called Castle Clash with a Tinderverified.com URL to make it seem legitimate. Their spamming attempts aimed to accelerate their downloads but ended up aggravating lots of users who believed they were actually talking to real people as you can see below: Figure 3: An example of a Tinder Bot tricking a user to visit a gaming website. A similar case also took place when someone used Tinder to collect Uber referral credits, which was also against Tinder's terms of service. As more and more of these cases emerge, it's clear that one of the greatest challenges for online dating platforms is learning to co-exist with AI and bots, as innocent or dangerous as they may be for users. As well as protecting their users, they also have to ensure they are themselves integrating AI within their applications to make online dating smarter - so that users don't even feel the need to download Bernie in the beginning. If they achieve that, then perhaps Sean Rad's number of daily swipes may drop in the years to come.

By Ramon Sangüesa, Data Transparency Lab coordinator. This week the 2016 edition of the Data Transparency Lab conference will take place. In this event, a community of technologists, researchers, policymakers and industry representatives come together at Columbia University in New York in their ambition to advance online personal data transparency through scientific research and design. This same conference took place last year in Boston at MIT as you can see below: Video: The DTL 2015 Conference in Boston The uncontrollable growth of the internet has outpaced our ability as individuals, societies and states to maintain control of our identity and privacy meaning that we need to define new guidelines for how our personal data is owned, accessed and used, according to the DTL website. The conference which kicks off tomorrow has several key objectives: Promote the concept of personal data transparency enabling users to have the right tools to know who, how, why and for what their data is being used. Provide a platform for the research and development of the new tools which allow this. Bring together researchers, regulators, industry leaders, designers, journalists and active players in the area of privacy and data transparency allowing their to be a interdisciplinary dialogue. As part of their strategy to achieve these objectives, the DTL gives 6 grants per year to projects which help them to achieve this goal to achieve online personal data transparency through scientific research. These projects are presently in different stages of development, however, we are particularly excited about the Facebook Data Valuation Tool (FDVT) which has been developed by a research team at the Carlos III University, led by Professor Angel Cuevas - which was recently featured in the El Confidencial newspaper. This video explains a little more about the potential of this tool: Video: The Facebook Data Valuation Tool explained As you can see in the video, this unique tool is an add-on for browsers which runs while you interact with Facebook. The FDVT estimates how much your activity on Facebook (browsing, posting, liking, clicking on adverts, etc.) is worth. To calculate this estimation the FDVT browser extension locates the ads you are being shown while the user is “inside” Facebook, calculating the value of this advertising impression throughout the session. And of course, this value grows if the user clicks on an advert within Facebook. One of the key findings of this tool is that it hints at higher revenues than the usual estimate for each user of Facebook throughout a whole year of usage. This has been estimated at approximately €10, however, it is easy to see that if you extrapolate the value generated in a short span of time devoted to using the FDVT, the final yearly value generated will be much higher. Figure 1: The DTL Conference 2016 takes place this week at Columbia University this week Beyond the direct effect of raising users awareness about the economy behind their personal data, this tool can have some other practical uses. We have also been approached by a research group in economics and international taxes. They understand that with a tool like this, it could be easier to estimate how much taxes a company such as Facebook should be paying in each country, just by segmenting data from the FDVT if is shared with a substantial number of users in different countries. Want to find out more about the FDVT? Check out Chema Alonso's take on his blog.