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]
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]
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]
In 1950, William Faulkner delivered a famous acceptance speech for the Nobel prize in literature in which he rallied for the “inexhaustible [human] voice” and his belief in its supremacy—not merely to endure but to prevail. Faulkner reasoned this was because the human voice, transmuted into art, possesses soul—a soul capable of compassion and sacrifice.In 1950, William Faulkner delivered a famous acceptance speech for the Nobel prize in literature in which he rallied for the “inexhaustible [human] voice” and his belief in its supremacy—not merely to endure but to prevail. Faulkner reasoned this was because the human voice, transmuted into art, possesses soul—a soul capable of compassion and sacrifice.Machine learning & AI[#item_full_content]
Northwestern University engineers have developed the first modular robots with athletic intelligence. They can be combined and recombined in the wild, recover from injury and keep moving no matter what’s thrown at them.Northwestern University engineers have developed the first modular robots with athletic intelligence. They can be combined and recombined in the wild, recover from injury and keep moving no matter what’s thrown at them.Machine learning & AI[#item_full_content]
The Pentagon’s designation of the industry-leading AI company Anthropic as a “supply chain risk” suggests that the U.S. government may be using its supply chain authority as leverage in negotiations with U.S. businesses, according to a Northeastern University expert.The Pentagon’s designation of the industry-leading AI company Anthropic as a “supply chain risk” suggests that the U.S. government may be using its supply chain authority as leverage in negotiations with U.S. businesses, according to a Northeastern University expert.Business[#item_full_content]
Computer vision technologies are artificial intelligence (AI)-powered systems that can capture, analyze, and interpret visual data captured from real-world environments. While these systems are now widely used, many of them perform poorly under some lighting conditions and when the light in captured scenes changes abruptly.Computer vision technologies are artificial intelligence (AI)-powered systems that can capture, analyze, and interpret visual data captured from real-world environments. While these systems are now widely used, many of them perform poorly under some lighting conditions and when the light in captured scenes changes abruptly.Hi Tech & Innovation[#item_full_content]
What if the thermal noise that hinders the efficiency of both classical and quantum computers could, instead, be used as a power source? What if computers could make use of the noise instead of suppressing or overcoming it? These are the goals of a relatively new branch of computing known as thermodynamic computing. A collaboration between researchers at the Molecular Foundry and the National Energy Research Scientific Computing Center (NERSC), both U.S. Department of Energy (DOE) user facilities located at Lawrence Berkeley National Laboratory (Berkeley Lab), is bringing them closer to reality.What if the thermal noise that hinders the efficiency of both classical and quantum computers could, instead, be used as a power source? What if computers could make use of the noise instead of suppressing or overcoming it? These are the goals of a relatively new branch of computing known as thermodynamic computing. A collaboration between researchers at the Molecular Foundry and the National Energy Research Scientific Computing Center (NERSC), both U.S. Department of Energy (DOE) user facilities located at Lawrence Berkeley National Laboratory (Berkeley Lab), is bringing them closer to reality.Energy & Green Tech[#item_full_content]
