With so many artificial intelligence (AI) products being offered now, it’s increasingly tempting to offload difficult thinking tasks to chatbots, agents and other tools.With so many artificial intelligence (AI) products being offered now, it’s increasingly tempting to offload difficult thinking tasks to chatbots, agents and other tools.Consumer & Gadgets[#item_full_content]
When a group of researchers at Northeastern University’s Bau Lab began toying with a new kind of autonomous artificial intelligence “agent,” it was supposed to be a fun weekend experiment. Instead, alarm bells started ringing. The more they tested the capabilities and limits of these AI models, which have persistent memory and can take some actions on their own, the more troubling behavior they witnessed.When a group of researchers at Northeastern University’s Bau Lab began toying with a new kind of autonomous artificial intelligence “agent,” it was supposed to be a fun weekend experiment. Instead, alarm bells started ringing. The more they tested the capabilities and limits of these AI models, which have persistent memory and can take some actions on their own, the more troubling behavior they witnessed.Machine learning & AI[#item_full_content]
French artificial intelligence startup AMI, co-founded by Meta’s former chief AI scientist Yann LeCun, announced Tuesday it has raised $1 billion to develop models able to understand the physical world.French artificial intelligence startup AMI, co-founded by Meta’s former chief AI scientist Yann LeCun, announced Tuesday it has raised $1 billion to develop models able to understand the physical world.Machine learning & AI[#item_full_content]
Every week brings fresh claims about AI transforming the workplace. A CEO declares a revolution. A think piece predicts millions of jobs vanishing overnight. The noise is relentless.Every week brings fresh claims about AI transforming the workplace. A CEO declares a revolution. A think piece predicts millions of jobs vanishing overnight. The noise is relentless.Machine learning & AI[#item_full_content]
RMIT University engineers in Australia have built a remote-controlled minibot that hoovers up oil spills using an innovative filtering system inspired by sea urchins. Oil spills are still a serious problem around the world. They can badly damage oceans and coasts, kill or injure sea animals and birds, and cost billions of dollars to clean up and repair the damage.RMIT University engineers in Australia have built a remote-controlled minibot that hoovers up oil spills using an innovative filtering system inspired by sea urchins. Oil spills are still a serious problem around the world. They can badly damage oceans and coasts, kill or injure sea animals and birds, and cost billions of dollars to clean up and repair the damage.[#item_full_content]
In a collaboration between Tianjin University and the Chinese University of Hong Kong, researchers led by Xiangbin Teng used behavioral and brain activity measures to explore whether people can discern between AI-generated and human speech. The researchers also assessed whether brief training improves this ability. This work is published in eNeuro.In a collaboration between Tianjin University and the Chinese University of Hong Kong, researchers led by Xiangbin Teng used behavioral and brain activity measures to explore whether people can discern between AI-generated and human speech. The researchers also assessed whether brief training improves this ability. This work is published in eNeuro.Security[#item_full_content]
Australian researchers have built an ultra-compact artificial intelligence (AI) chip that is able to make calculations using the power of light, at the speed of light. The nano photonic chip prototype, which harnesses the power of light particles (photons) is built completely in-house at the Sydney Nano Hub at the University of Sydney. The researchers say the prototype could play an important role in developing more energy-efficient AI hardware as global demand for artificial intelligence continues to grow, potentially lowering the overall energy footprint of future computing systems.Australian researchers have built an ultra-compact artificial intelligence (AI) chip that is able to make calculations using the power of light, at the speed of light. The nano photonic chip prototype, which harnesses the power of light particles (photons) is built completely in-house at the Sydney Nano Hub at the University of Sydney. The researchers say the prototype could play an important role in developing more energy-efficient AI hardware as global demand for artificial intelligence continues to grow, potentially lowering the overall energy footprint of future computing systems.Hardware[#item_full_content]
Artificial intelligence now plays Go, paints pictures, and even converses like a human. However, there remains a decisive difference: AI requires far more electricity than the human brain to operate. Scientists have long asked the question, “How can the brain learn so intelligently using so little energy?” KAIST researchers have moved one step closer to the answer.Artificial intelligence now plays Go, paints pictures, and even converses like a human. However, there remains a decisive difference: AI requires far more electricity than the human brain to operate. Scientists have long asked the question, “How can the brain learn so intelligently using so little energy?” KAIST researchers have moved one step closer to the answer.[#item_full_content]
Artificial intelligence now plays Go, paints pictures, and even converses like a human. However, there remains a decisive difference: AI requires far more electricity than the human brain to operate. Scientists have long asked the question, “How can the brain learn so intelligently using so little energy?” KAIST researchers have moved one step closer to the answer.Artificial intelligence now plays Go, paints pictures, and even converses like a human. However, there remains a decisive difference: AI requires far more electricity than the human brain to operate. Scientists have long asked the question, “How can the brain learn so intelligently using so little energy?” KAIST researchers have moved one step closer to the answer.Computer Sciences[#item_full_content]
In high-stakes settings like medical diagnostics, users often want to know what led a computer vision model to make a certain prediction, so they can determine whether to trust its output. Concept bottleneck modeling is one method that enables artificial intelligence systems to explain their decision-making process. These methods force a deep-learning model to use a set of concepts, which can be understood by humans, to make a prediction. In new research, MIT computer scientists developed a method that coaxes the model to achieve better accuracy and clearer, more concise explanations.In high-stakes settings like medical diagnostics, users often want to know what led a computer vision model to make a certain prediction, so they can determine whether to trust its output. Concept bottleneck modeling is one method that enables artificial intelligence systems to explain their decision-making process. These methods force a deep-learning model to use a set of concepts, which can be understood by humans, to make a prediction. In new research, MIT computer scientists developed a method that coaxes the model to achieve better accuracy and clearer, more concise explanations.[#item_full_content]
