In our hyper-connected world, we rely on encrypted communications every day—to shop online, digitally sign documents, make bank transactions, check our steps on fitness trackers.In our hyper-connected world, we rely on encrypted communications every day—to shop online, digitally sign documents, make bank transactions, check our steps on fitness trackers.[#item_full_content]

Even with all its training and computer power, an artificial intelligence (AI) tool like ChatGPT can’t represent the concept of a flower the way a human does, according to a new study.Even with all its training and computer power, an artificial intelligence (AI) tool like ChatGPT can’t represent the concept of a flower the way a human does, according to a new study.[#item_full_content]

In an increasingly digitized and connected environment, the demand for computer programmers continues to grow and so does the need for training to produce new coding specialists. Often, they are professionals from other sectors who want to switch career paths. In these cases, the acquisition of computational thinking and programming skills is of key importance for them to succeed in this process.In an increasingly digitized and connected environment, the demand for computer programmers continues to grow and so does the need for training to produce new coding specialists. Often, they are professionals from other sectors who want to switch career paths. In these cases, the acquisition of computational thinking and programming skills is of key importance for them to succeed in this process.[#item_full_content]

When you’re trying to communicate or understand ideas, words don’t always do the trick. Sometimes the more efficient approach is to do a simple sketch of that concept—for example, diagramming a circuit might help make sense of how the system works.When you’re trying to communicate or understand ideas, words don’t always do the trick. Sometimes the more efficient approach is to do a simple sketch of that concept—for example, diagramming a circuit might help make sense of how the system works.[#item_full_content]

Imagine asking a conversational bot like Claude or ChatGPT a legal question in Greek about local traffic regulations. Within seconds, it replies in fluent Greek with an answer based on UK law. The model understood the language, but not the jurisdiction. This kind of failure illustrates the inability of large language models (LLMs) to understand regional, cultural and, in this case, legal knowledge, while at the same time being proficient in many of the world’s languages.Imagine asking a conversational bot like Claude or ChatGPT a legal question in Greek about local traffic regulations. Within seconds, it replies in fluent Greek with an answer based on UK law. The model understood the language, but not the jurisdiction. This kind of failure illustrates the inability of large language models (LLMs) to understand regional, cultural and, in this case, legal knowledge, while at the same time being proficient in many of the world’s languages.[#item_full_content]

The ability to communicate effectively in spoken English is a key determinant of both academic and professional success. Traditionally, the degree of mastery over English grammar, vocabulary, pronunciation, and communication skills has been assessed through tedious and expensive human-administered tests.The ability to communicate effectively in spoken English is a key determinant of both academic and professional success. Traditionally, the degree of mastery over English grammar, vocabulary, pronunciation, and communication skills has been assessed through tedious and expensive human-administered tests.[#item_full_content]

As artificial intelligence and smart devices continue to evolve, machine vision is taking an increasingly pivotal role as a key enabler of modern technologies. Unfortunately, despite much progress, machine vision systems still face a major problem: Processing the enormous amounts of visual data generated every second requires substantial power, storage, and computational resources. This limitation makes it difficult to deploy visual recognition capabilities in edge devices, such as smartphones, drones, or autonomous vehicles.As artificial intelligence and smart devices continue to evolve, machine vision is taking an increasingly pivotal role as a key enabler of modern technologies. Unfortunately, despite much progress, machine vision systems still face a major problem: Processing the enormous amounts of visual data generated every second requires substantial power, storage, and computational resources. This limitation makes it difficult to deploy visual recognition capabilities in edge devices, such as smartphones, drones, or autonomous vehicles.[#item_full_content]

Over the past decades, roboticists have introduced various systems that can replicate specific human motions and behaviors with remarkable accuracy. Some of these robots can even compete with other robots or humans in specific sports, such as the robots showcased at the RoboCup, an international robotics event at which robots play soccer with each other.Over the past decades, roboticists have introduced various systems that can replicate specific human motions and behaviors with remarkable accuracy. Some of these robots can even compete with other robots or humans in specific sports, such as the robots showcased at the RoboCup, an international robotics event at which robots play soccer with each other.[#item_full_content]

As artificial intelligence takes off, how do we efficiently integrate it into our lives and our work? Bridging the gap between promise and practice, Jann Spiess, an associate professor of operations, information, and technology at Stanford Graduate School of Business, is exploring how algorithms can be designed to most effectively support—rather than replace—human decision-makers.As artificial intelligence takes off, how do we efficiently integrate it into our lives and our work? Bridging the gap between promise and practice, Jann Spiess, an associate professor of operations, information, and technology at Stanford Graduate School of Business, is exploring how algorithms can be designed to most effectively support—rather than replace—human decision-makers.[#item_full_content]

Teaching AI to explore its surroundings is a bit like teaching a robot to find treasure in a vast maze—it needs to try different paths, but some lead nowhere. In many real-world challenges, like training robots or playing complex games, rewards are few and far between, making it easy for AI to waste time on dead ends.Teaching AI to explore its surroundings is a bit like teaching a robot to find treasure in a vast maze—it needs to try different paths, but some lead nowhere. In many real-world challenges, like training robots or playing complex games, rewards are few and far between, making it easy for AI to waste time on dead ends.[#item_full_content]