Latest news with #A.M.TuringAward
Yahoo
13 hours ago
- Business
- Yahoo
Yoshua Bengio Launches LawZero: A New Nonprofit Advancing Safe-by-Design AI
MONTRÉAL, June 3, 2025 /CNW/ - Yoshua Bengio, the most-cited artificial intelligence (AI) researcher in the world and A.M. Turing Award winner, today announced the launch of LawZero, a new nonprofit organization committed to advancing research and developing technical solutions for safe-by-design AI systems. LawZero is assembling a world-class team of AI researchers who are building the next generation of AI systems in an environment dedicated to prioritizing safety over commercial imperatives. The organization was founded in response to evidence that today's frontier AI models are developing dangerous capabilities and behaviours, including deception, self-preservation, and goal misalignment. LawZero's work will help to unlock the immense potential of AI in ways that reduce the likelihood of a range of known dangers associated with today's systems, including algorithmic bias, intentional misuse, and loss of human control. LawZero is structured as a nonprofit organization to ensure it is insulated from market and government pressures, which risk compromising AI safety. The organization is also pulling together a seasoned leadership team to drive this ambitious mission forward. "LawZero is the result of the new scientific direction I undertook in 2023, after recognizing the rapid progress made by private labs toward Artificial General Intelligence and beyond, as well as its profound implications for humanity," said Yoshua Bengio, President and Scientific Director at LawZero. "Current frontier systems are already showing signs of self-preservation and deceptive behaviours, and this will only accelerate as their capabilities and degree of agency increase. LawZero is my team's constructive response to these challenges. It's an approach to AI that is not only powerful but also fundamentally safe. At LawZero, we believe that at the heart of every AI frontier system, there should be one guiding principle above all: The protection of human joy and endeavour." Scientist AI: a new model for safer artificial intelligence LawZero has a growing technical team of over 15 researchers, pioneering a radically new approach called Scientist AI, a practical, effective and more secure alternative to today's uncontrolled agentic AI systems. Scientist AI stands apart from the approaches of frontier AI companies, which are increasingly focused on developing agentic systems. Scientist AIs are non-agentic and primarily learn to understand the world rather than act in it, giving truthful answers to questions based on transparent externalized reasoning. Such AI systems could be used to provide oversight for agentic AI systems, accelerate scientific discovery, and advance the understanding of AI risks and how to avoid them. Major institutions and individuals, including the Future of Life Institute, Jaan Tallinn, Open Philanthropy, Schmidt Sciences, and Silicon Valley Community Foundation have made donations to the project as part of its incubation phase. About LawZero LawZero is a nonprofit organization committed to advancing research and creating technical solutions that enable safe-by-design AI systems. Its scientific direction is based on new research and methods led by Professor Yoshua Bengio, the most cited AI researcher in the world. Based in Montréal, LawZero's research aims to build non-agentic AI that could be used to accelerate scientific discovery, to provide oversight for agentic AI systems, and to advance the understanding of AI risks and how to avoid them. LawZero believes that AI should be cultivated as a global public good—developed and used safely towards human flourishing. LawZero was incubated at Mila - Quebec AI Institute, a non-profit founded by Professor Bengio. Mila now serves as LawZero's operating partner. For more information, visit View original content to download multimedia: SOURCE LawZero View original content to download multimedia: Sign in to access your portfolio
Cision Canada
13 hours ago
- Business
- Cision Canada
Yoshua Bengio Launches LawZero: A New Nonprofit Advancing Safe-by-Design AI Français
MONTRÉAL, June 3, 2025 /CNW/ - Yoshua Bengio, the most-cited artificial intelligence (AI) researcher in the world and A.M. Turing Award winner, today announced the launch of LawZero, a new nonprofit organization committed to advancing research and developing technical solutions for safe-by-design AI systems. LawZero is assembling a world-class team of AI researchers who are building the next generation of AI systems in an environment dedicated to prioritizing safety over commercial imperatives. The organization was founded in response to evidence that today's frontier AI models are developing dangerous capabilities and behaviours, including deception, self-preservation, and goal misalignment. LawZero's work will help to unlock the immense potential of AI in ways that reduce the likelihood of a range of known dangers associated with today's systems, including algorithmic bias, intentional misuse, and loss of human control. LawZero is structured as a nonprofit organization to ensure it is insulated from market and government pressures, which risk compromising AI safety. The organization is also pulling together a seasoned leadership team to drive this ambitious mission forward. "LawZero is the result of the new scientific direction I undertook in 2023, after recognizing the rapid progress made by private labs toward Artificial General Intelligence and beyond, as well as its profound implications for humanity," said Yoshua Bengio, President and Scientific Director at LawZero. "Current frontier systems are already showing signs of self-preservation and deceptive behaviours, and this will only accelerate as their capabilities and degree of agency increase. LawZero is my team's constructive response to these challenges. It's an approach to AI that is not only powerful but also fundamentally safe. At LawZero, we believe that at the heart of every AI frontier system, there should be one guiding principle above all: The protection of human joy and endeavour." Scientist AI: a new model for safer artificial intelligence LawZero has a growing technical team of over 15 researchers, pioneering a radically new approach called Scientist AI, a practical, effective and more secure alternative to today's uncontrolled agentic AI systems. Scientist AI stands apart from the approaches of frontier AI companies, which are increasingly focused on developing agentic systems. Scientist AIs are non-agentic and primarily learn to understand the world rather than act in it, giving truthful answers to questions based on transparent externalized reasoning. Such AI systems could be used to provide oversight for agentic AI systems, accelerate scientific discovery, and advance the understanding of AI risks and how to avoid them. Major institutions and individuals, including the Future of Life Institute, Jaan Tallinn, Open Philanthropy, Schmidt Sciences, and Silicon Valley Community Foundation have made donations to the project as part of its incubation phase. About LawZero LawZero is a nonprofit organization committed to advancing research and creating technical solutions that enable safe-by-design AI systems. Its scientific direction is based on new research and methods led by Professor Yoshua Bengio, the most cited AI researcher in the world. Based in Montréal, LawZero's research aims to build non-agentic AI that could be used to accelerate scientific discovery, to provide oversight for agentic AI systems, and to advance the understanding of AI risks and how to avoid them. LawZero believes that AI should be cultivated as a global public good—developed and used safely towards human flourishing. LawZero was incubated at Mila - Quebec AI Institute, a non-profit founded by Professor Bengio. Mila now serves as LawZero's operating partner. For more information, visit
Yahoo
05-03-2025
- Science
- Yahoo
AI pioneers who channeled 'hedonistic' machines win computer science's top prize
Teaching machines in the way that animal trainers mold the behavior of dogs or horses has been an important method for developing artificial intelligence and one that was recognized Wednesday with the top computer science award. Two pioneers in the field of reinforcement learning, Andrew Barto and Richard Sutton, are the winners of this year's A.M. Turing Award, the tech world's equivalent of the Nobel Prize. Research that Barto, 76, and Sutton, 67, began in the late 1970s paved the way for some of the past decade's AI breakthroughs. At the heart of their work was channeling so-called 'hedonistic' machines that could continuously adapt their behavior in response to positive signals. See for yourself — The Yodel is the go-to source for daily news, entertainment and feel-good stories. By signing up, you agree to our Terms and Privacy Policy. Reinforcement learning is what led a Google computer program to beat the world's best human players of the ancient Chinese board game Go in 2016 and 2017. It's also been a key technique in improving popular AI tools like ChatGPT, optimizing financial trading and helping a robotic hand solve a Rubik's Cube. But Barto said the field was "not fashionable' when he and his doctoral student, Sutton, began crafting their theories and algorithms at the University of Massachusetts, Amherst. 'We were kind of in the wilderness,' Barto said in an interview with The Associated Press. 'Which is why it's so gratifying to receive this award, to see this becoming more recognized as something relevant and interesting. In the early days, it was not.' Google sponsors the annual $1 million prize, which was announced Wednesday by the Association for Computing Machinery. Barto, now retired from the University of Massachusetts, and Sutton, a longtime professor at Canada's University of Alberta, aren't the first AI pioneers to win the award named after British mathematician, codebreaker and early AI thinker Alan Turing. But their research has directly sought to answer Turing's 1947 call for a machine that 'can learn from experience' — which Sutton describes as 'arguably the essential idea of reinforcement learning.' In particular, they borrowed from ideas in psychology and neuroscience about the way that pleasure-seeking neurons respond to rewards or punishment. In one landmark paper published in the early 1980s, Barto and Sutton set their new approach on a specific task in a simulated world: balance a pole on a moving cart to keep it from falling. The two computer scientists later co-authored a widely used textbook on reinforcement learning. 'The tools they developed remain a central pillar of the AI boom and have rendered major advances, attracted legions of young researchers, and driven billions of dollars in investments,' said Google's chief scientist Jeff Dean in a written statement. In a joint interview with the AP, Barto and Sutton didn't always agree on how to evaluate the risks of AI agents that are constantly seeking to improve themselves. They also distinguished their work from the branch of generative AI technology that is currently in fashion — the large language models behind chatbots made by OpenAI, Google and other tech giants that mimic human writing and other media. 'The big choice is, do you try to learn from people's data, or do you try to learn from an (AI) agent's own life and its own experience?' Sutton said. Sutton has dismissed what he describes as overblown concerns about AI's threat to humanity, while Barto disagreed and said 'You have to be cognizant of potential unexpected consequences.' Barto, retired for 14 years, describes himself as a Luddite, while Sutton is embracing a future he expects to have beings of greater intelligence than current humans — an idea sometimes known as posthumanism. 'People are machines. They're amazing, wonderful machines,' but they are also not the 'end product' and could work better, Sutton said. 'It's intrinsically a part of the AI enterprise,' Sutton said. 'We're trying to understand ourselves and, of course, to make things that can work even better. Maybe to become such things.'
The Hill
05-03-2025
- Science
- The Hill
AI pioneers who channeled ‘hedonistic' machines win computer science's top prize
Teaching machines in the way that animal trainers mold the behavior of dogs or horses has been an important method for developing artificial intelligence and one that was recognized Wednesday with the top computer science award. Two pioneers in the field of reinforcement learning, Andrew Barto and Richard Sutton, are the winners of this year's A.M. Turing Award, the tech world's equivalent of the Nobel Prize. Research that Barto, 76, and Sutton, 67, began in the late 1970s paved the way for some of the past decade's AI breakthroughs. At the heart of their work was channeling so-called 'hedonistic' machines that could continuously adapt their behavior in response to positive signals. Reinforcement learning is what led a Google computer program to beat the world's best human players of the ancient Chinese board game Go in 2016 and 2017. It's also been a key technique in improving popular AI tools like ChatGPT, optimizing financial trading and helping a robotic hand solve a Rubik's Cube. But Barto said the field was 'not fashionable' when he and his doctoral student, Sutton, began crafting their theories and algorithms at the University of Massachusetts, Amherst. 'We were kind of in the wilderness,' Barto said in an interview with The Associated Press. 'Which is why it's so gratifying to receive this award, to see this becoming more recognized as something relevant and interesting. In the early days, it was not.' Google sponsors the annual $1 million prize, which was announced Wednesday by the Association for Computing Machinery. Barto, now retired from the University of Massachusetts, and Sutton, a longtime professor at Canada's University of Alberta, aren't the first AI pioneers to win the award named after British mathematician, codebreaker and early AI thinker Alan Turing. But their research has directly sought to answer Turing's 1947 call for a machine that 'can learn from experience' — which Sutton describes as 'arguably the essential idea of reinforcement learning.' In particular, they borrowed from ideas in psychology and neuroscience about the way that pleasure-seeking neurons respond to rewards or punishment. In one landmark paper published in the early 1980s, Barto and Sutton set their new approach on a specific task in a simulated world: balance a pole on a moving cart to keep it from falling. The two computer scientists later co-authored a widely used textbook on reinforcement learning. 'The tools they developed remain a central pillar of the AI boom and have rendered major advances, attracted legions of young researchers, and driven billions of dollars in investments,' said Google's chief scientist Jeff Dean in a written statement. In a joint interview with the AP, Barto and Sutton didn't always agree on how to evaluate the risks of AI agents that are constantly seeking to improve themselves. They also distinguished their work from the branch of generative AI technology that is currently in fashion — the large language models behind chatbots made by OpenAI, Google and other tech giants that mimic human writing and other media. 'The big choice is, do you try to learn from people's data, or do you try to learn from an (AI) agent's own life and its own experience?' Sutton said. Sutton has dismissed what he describes as overblown concerns about AI's threat to humanity, while Barto disagreed and said 'You have to be cognizant of potential unexpected consequences.' Barto, retired for 14 years, describes himself as a Luddite, while Sutton is embracing a future he expects to have beings of greater intelligence than current humans — an idea sometimes known as posthumanism. 'People are machines. They're amazing, wonderful machines,' but they are also not the 'end product' and could work better, Sutton said. 'It's intrinsically a part of the AI enterprise,' Sutton said. 'We're trying to understand ourselves and, of course, to make things that can work even better. Maybe to become such things.'
Associated Press
05-03-2025
- Science
- Associated Press
AI pioneers who channeled ‘hedonistic' machines win computer science's top prize
Teaching machines in the way that animal trainers mold the behavior of dogs or horses has been an important method for developing artificial intelligence and one that was recognized Wednesday with the top computer science award. Two pioneers in the field of reinforcement learning, Andrew Barto and Richard Sutton, are the winners of this year's A.M. Turing Award, the tech world's equivalent of the Nobel Prize. Research that Barto, 76, and Sutton, 67, began in the late 1970s paved the way for some of the past decade's AI breakthroughs. At the heart of their work was channeling so-called 'hedonistic' machines that could continuously adapt their behavior in response to positive signals. Reinforcement learning is what led a Google computer program to beat the world's best human players of the ancient Chinese board game Go in 2016 and 2017. It's also been a key technique in improving popular AI tools like ChatGPT, optimizing financial trading and helping a robotic hand solve a Rubik's Cube. But Barto said the field was 'not fashionable' when he and his doctoral student, Sutton, began crafting their theories and algorithms at the University of Massachusetts, Amherst. 'We were kind of in the wilderness,' Barto said in an interview with The Associated Press. 'Which is why it's so gratifying to receive this award, to see this becoming more recognized as something relevant and interesting. In the early days, it was not.' Google sponsors the annual $1 million prize, which was announced Wednesday by the Association for Computing Machinery. Barto, now retired from the University of Massachusetts, and Sutton, a longtime professor at Canada's University of Alberta, aren't the first AI pioneers to win the award named after British mathematician, codebreaker and early AI thinker Alan Turing. But their research has directly sought to answer Turing's 1947 call for a machine that 'can learn from experience' — which Sutton describes as 'arguably the essential idea of reinforcement learning.' In particular, they borrowed from ideas in psychology and neuroscience about the way that pleasure-seeking neurons respond to rewards or punishment. In one landmark paper published in the early 1980s, Barto and Sutton set their new approach on a specific task in a simulated world: balance a pole on a moving cart to keep it from falling. The two computer scientists later co-authored a widely used textbook on reinforcement learning. 'The tools they developed remain a central pillar of the AI boom and have rendered major advances, attracted legions of young researchers, and driven billions of dollars in investments,' said Google's chief scientist Jeff Dean in a written statement. In a joint interview with the AP, Barto and Sutton didn't always agree on how to evaluate the risks of AI agents that are constantly seeking to improve themselves. They also distinguished their work from the branch of generative AI technology that is currently in fashion — the large language models behind chatbots made by OpenAI, Google and other tech giants that mimic human writing and other media. 'The big choice is, do you try to learn from people's data, or do you try to learn from an (AI) agent's own life and its own experience?' Sutton said. Sutton has dismissed what he describes as overblown concerns about AI's threat to humanity, while Barto disagreed and said 'You have to be cognizant of potential unexpected consequences.' Barto, retired for 14 years, describes himself as a Luddite, while Sutton is embracing a future he expects to have beings of greater intelligence than current humans — an idea sometimes known as posthumanism. 'People are machines. They're amazing, wonderful machines,' but they are also not the 'end product' and could work better, Sutton said. 'It's intrinsically a part of the AI enterprise,' Sutton said. 'We're trying to understand ourselves and, of course, to make things that can work even better. Maybe to become such things.'
