How inconvenient would it be if you had to manually transfer every contact and photo from scratch every time you switched to a new smartphone? Current artificial intelligence (AI) models face a similar predicament. Whenever a superior new AI model—such as a new version of ChatGPT—emerges, it has to be retrained with massive amounts of data and at a high cost to acquire specialized knowledge in specific fields. Now a Korean research team has developed a “knowledge transplantation” technology between AI models that can resolve this inefficiency.How inconvenient would it be if you had to manually transfer every contact and photo from scratch every time you switched to a new smartphone? Current artificial intelligence (AI) models face a similar predicament. Whenever a superior new AI model—such as a new version of ChatGPT—emerges, it has to be retrained with massive amounts of data and at a high cost to acquire specialized knowledge in specific fields. Now a Korean research team has developed a “knowledge transplantation” technology between AI models that can resolve this inefficiency.[#item_full_content]

While popular AI models such as ChatGPT are trained on language or photographs, new models created by researchers from the Polymathic AI collaboration are trained using real scientific datasets. The models are already using knowledge from one field to address seemingly completely different problems in another.While popular AI models such as ChatGPT are trained on language or photographs, new models created by researchers from the Polymathic AI collaboration are trained using real scientific datasets. The models are already using knowledge from one field to address seemingly completely different problems in another.[#item_full_content]

For half a century, computing advanced in a reassuring, predictable way. Transistors—devices used to switch electrical signals on a computer chip—became smaller. Consequently, computer chips became faster, and society quietly assimilated the gains almost without noticing.For half a century, computing advanced in a reassuring, predictable way. Transistors—devices used to switch electrical signals on a computer chip—became smaller. Consequently, computer chips became faster, and society quietly assimilated the gains almost without noticing.[#item_full_content]

Generative AI is reshaping software development—and fast. A new study published in Science shows that AI-assisted coding is spreading rapidly, though unevenly: in the U.S., the share of new code relying on AI rose from 5% in 2022 to 29% in early 2025, compared with just 12% in China. AI usage is highest among less experienced programmers, but productivity gains go to seasoned developers.Generative AI is reshaping software development—and fast. A new study published in Science shows that AI-assisted coding is spreading rapidly, though unevenly: in the U.S., the share of new code relying on AI rose from 5% in 2022 to 29% in early 2025, compared with just 12% in China. AI usage is highest among less experienced programmers, but productivity gains go to seasoned developers.[#item_full_content]

Large language models (LLMs), the computational models underpinning the functioning of ChatGPT, Gemini and other widely used artificial intelligence (AI) platforms, can rapidly source information and generate texts tailored for specific purposes. As these models are trained on large amounts of texts written by humans, they could exhibit some human-like biases, which are inclinations to prefer specific stimuli, ideas or groups that deviate from objectivity.Large language models (LLMs), the computational models underpinning the functioning of ChatGPT, Gemini and other widely used artificial intelligence (AI) platforms, can rapidly source information and generate texts tailored for specific purposes. As these models are trained on large amounts of texts written by humans, they could exhibit some human-like biases, which are inclinations to prefer specific stimuli, ideas or groups that deviate from objectivity.[#item_full_content]

The vision of a fully connected world is rapidly becoming a reality through the Internet of Things (IoT)—a growing network of physical devices that collect and share data over the Internet, including everything from small sensors to autonomous vehicles and industrial equipment.The vision of a fully connected world is rapidly becoming a reality through the Internet of Things (IoT)—a growing network of physical devices that collect and share data over the Internet, including everything from small sensors to autonomous vehicles and industrial equipment.[#item_full_content]

A study led by UC Riverside researchers offers a practical fix to one of artificial intelligence’s toughest challenges by enabling AI systems to reason more like humans—without requiring new training data beyond test questions.A study led by UC Riverside researchers offers a practical fix to one of artificial intelligence’s toughest challenges by enabling AI systems to reason more like humans—without requiring new training data beyond test questions.[#item_full_content]

Are generative artificial intelligence systems such as ChatGPT truly creative? A research team led by Professor Karim Jerbi from the Department of Psychology at the Université de Montréal, and including AI pioneer Yoshua Bengio, also a professor at Université de Montréal, has just published the largest comparative study ever conducted on the creativity of large language models versus humans.Are generative artificial intelligence systems such as ChatGPT truly creative? A research team led by Professor Karim Jerbi from the Department of Psychology at the Université de Montréal, and including AI pioneer Yoshua Bengio, also a professor at Université de Montréal, has just published the largest comparative study ever conducted on the creativity of large language models versus humans.[#item_full_content]

Emotions are a fundamental part of human psychology—a complex process that has long distinguished us from machines. Even advanced artificial intelligence (AI) lacks the capacity to feel. However, researchers are now exploring whether the formation of emotions can be computationally modeled, providing machines with a deeper, more human-like understanding of emotional states.Emotions are a fundamental part of human psychology—a complex process that has long distinguished us from machines. Even advanced artificial intelligence (AI) lacks the capacity to feel. However, researchers are now exploring whether the formation of emotions can be computationally modeled, providing machines with a deeper, more human-like understanding of emotional states.[#item_full_content]

MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to test whenever a model is deployed in a new setting.MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to test whenever a model is deployed in a new setting.[#item_full_content]