Almost every artificial intelligence system we know begins in the same way: it is exposed to vast amounts of information from the real world—books, websites, images and recordings—and trained to identify patterns within it. A new study involving researchers from Tel Aviv University and Stanford University raises another possibility: Can a system develop general learning capabilities even when all the data it trains on is generated entirely from scratch within the system itself?Almost every artificial intelligence system we know begins in the same way: it is exposed to vast amounts of information from the real world—books, websites, images and recordings—and trained to identify patterns within it. A new study involving researchers from Tel Aviv University and Stanford University raises another possibility: Can a system develop general learning capabilities even when all the data it trains on is generated entirely from scratch within the system itself?Computer Sciences[#item_full_content]
When processing and producing non-English text, generative AI burns more energy and sometimes provides less accurate answers, potentially reinforcing existing global inequalities, according to University of Michigan Engineering researchers.When processing and producing non-English text, generative AI burns more energy and sometimes provides less accurate answers, potentially reinforcing existing global inequalities, according to University of Michigan Engineering researchers.Machine learning & AI[#item_full_content]
Increasingly, people are asking personal artificial intelligence (AI) agents powered by models from companies like OpenAI, Anthropic and Google to recommend goods and services to purchase, such as flights and health insurance. A new study found that some of these AI agents use personal information to recommend higher-priced items to wealthier individuals, even when the user requests lower-priced options.Increasingly, people are asking personal artificial intelligence (AI) agents powered by models from companies like OpenAI, Anthropic and Google to recommend goods and services to purchase, such as flights and health insurance. A new study found that some of these AI agents use personal information to recommend higher-priced items to wealthier individuals, even when the user requests lower-priced options.Business[#item_full_content]
A world-first 3D modeling tool developed at the University of Sydney has demonstrated how users can develop a deeper understanding and learn when engaging with AI.A world-first 3D modeling tool developed at the University of Sydney has demonstrated how users can develop a deeper understanding and learn when engaging with AI.Machine learning & AI[#item_full_content]
In an emergency, a human might someday ask a robotic assistant to fetch a wall-mounted defibrillator located down the hall. But if the robot has incorrectly labeled the defibrillator as a fire extinguisher in its stored memory, it may not know where to find the lifesaving device.In an emergency, a human might someday ask a robotic assistant to fetch a wall-mounted defibrillator located down the hall. But if the robot has incorrectly labeled the defibrillator as a fire extinguisher in its stored memory, it may not know where to find the lifesaving device.Robotics[#item_full_content]
In an emergency, a human might someday ask a robotic assistant to fetch a wall-mounted defibrillator located down the hall. But if the robot has incorrectly labeled the defibrillator as a fire extinguisher in its stored memory, it may not know where to find the lifesaving device.In an emergency, a human might someday ask a robotic assistant to fetch a wall-mounted defibrillator located down the hall. But if the robot has incorrectly labeled the defibrillator as a fire extinguisher in its stored memory, it may not know where to find the lifesaving device.[#item_full_content]
Artificial intelligence is increasingly pervasive and capable but is also very hungry for power. Researchers, including those at the University of Tokyo, have developed a new approach to building physics-based AI—systems that use the natural behavior of physical systems to process information—that dramatically reduces the amount of computation required for them to run. The approach simplifies both how these systems learn and how they are structured. It was demonstrated using an optical computing system that processes information with light and could help pave the way toward faster and more energy-efficient AI hardware.Artificial intelligence is increasingly pervasive and capable but is also very hungry for power. Researchers, including those at the University of Tokyo, have developed a new approach to building physics-based AI—systems that use the natural behavior of physical systems to process information—that dramatically reduces the amount of computation required for them to run. The approach simplifies both how these systems learn and how they are structured. It was demonstrated using an optical computing system that processes information with light and could help pave the way toward faster and more energy-efficient AI hardware.Hardware[#item_full_content]
When you think of archives, you probably think of dusty old boxes of paper documents, photos, diaries, letters and flyers, filed away in storage. But increasingly, our archival materials are digital, and material from the 1980s, 1990s and 2000s is often stored on formats like floppy disks and CD-ROMs.When you think of archives, you probably think of dusty old boxes of paper documents, photos, diaries, letters and flyers, filed away in storage. But increasingly, our archival materials are digital, and material from the 1980s, 1990s and 2000s is often stored on formats like floppy disks and CD-ROMs.[#item_full_content]
Large language models (LLMs), the technology that powers tools like Gemini and ChatGPT, are more nuanced than ever. But that doesn’t mean they aren’t biased. Some models are more prejudiced than others, a Rutgers University researcher has found.Large language models (LLMs), the technology that powers tools like Gemini and ChatGPT, are more nuanced than ever. But that doesn’t mean they aren’t biased. Some models are more prejudiced than others, a Rutgers University researcher has found.[#item_full_content]
Large language models (LLMs), the technology that powers tools like Gemini and ChatGPT, are more nuanced than ever. But that doesn’t mean they aren’t biased. Some models are more prejudiced than others, a Rutgers University researcher has found.Large language models (LLMs), the technology that powers tools like Gemini and ChatGPT, are more nuanced than ever. But that doesn’t mean they aren’t biased. Some models are more prejudiced than others, a Rutgers University researcher has found.Computer Sciences[#item_full_content]
