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]
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.Computer Sciences[#item_full_content]
A dubious link from a friend. A headline too sensational to be true. A video that seems fake but you can’t be sure. As online misinformation grows harder to detect, new artificial-intelligence tools promise to help us separate fact from fiction. But do they actually work?A dubious link from a friend. A headline too sensational to be true. A video that seems fake but you can’t be sure. As online misinformation grows harder to detect, new artificial-intelligence tools promise to help us separate fact from fiction. But do they actually work?Security[#item_full_content]
Engineers at Oxford University have developed a rapid, ultra-low-cost method for manufacturing soft robots using common lab equipment. The method has been published in Advanced Science. The new technique enables researchers to fabricate soft robotic actuators—the flexible components that power movement—in under 10 minutes at a material cost of less than $0.10 (US Dollars) per unit.Engineers at Oxford University have developed a rapid, ultra-low-cost method for manufacturing soft robots using common lab equipment. The method has been published in Advanced Science. The new technique enables researchers to fabricate soft robotic actuators—the flexible components that power movement—in under 10 minutes at a material cost of less than $0.10 (US Dollars) per unit.[#item_full_content]
With only 2,200 people still speaking the Manx language, Chris Bartley is using AI text-to-speech systems to protect and showcase the heritage of endangered languages. Bartley, a School of Computer Science Ph.D. student at the University of Sheffield, has developed a speech and language AI text-to-speech system for endangered languages, with a particular focus upon Manx, the heritage language of the Isle of Man, where he originates from.With only 2,200 people still speaking the Manx language, Chris Bartley is using AI text-to-speech systems to protect and showcase the heritage of endangered languages. Bartley, a School of Computer Science Ph.D. student at the University of Sheffield, has developed a speech and language AI text-to-speech system for endangered languages, with a particular focus upon Manx, the heritage language of the Isle of Man, where he originates from.Machine learning & AI[#item_full_content]
