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cial issues AI presents. The collision between opposing perspectives is salutary and exhilarating; some of these figures, such as computer scientist Stuart Russell, Skype co-founder Jaan Tallinn, and physicist Max Tegmark, are deeply concerned with the threat of AI, including the existential one, while others, n
nces are intimately bound up in the idea of an impending technological singularity. His work on neuroscience and his initial support of McCulloch and Pitts adumbrated the startlingly effective deep-learning methods of the present day. Over the past decade, and particularly in the last five years, such de
me with a score in the game, and in some cases it finds a loophole that it exploits to gain infinitely many points without actually winning the race. Stuart Russell and Peter Norvig give a beautiful example in their book Artificial Intelligence: A Modern Approach: rewarding a vacuuming robot for how much dust it
ow it an abstract painting and see what it says. But it does a pretty good job. It works using the same neural-network technology that McCulloch and Pitts imagined in 1943 and lots of us worked on in the early eighties. Back in the 1980s, people successfully did OCR—optical character recognition. They t
cial issues AI presents. The collision between opposing perspectives is salutary and exhilarating; some of these figures, such as computer scientist Stuart Russell, Skype co-founder Jaan Tallinn, and physicist Max Tegmark, are deeply concerned with the threat of AI, including the existential one, while others, n
nces are intimately bound up in the idea of an impending technological singularity. His work on neuroscience and his initial support of McCulloch and Pitts adumbrated the startlingly effective deep-learning methods of the present day. Over the past decade, and particularly in the last five years, such de
me with a score in the game, and in some cases it finds a loophole that it exploits to gain infinitely many points without actually winning the race. Stuart Russell and Peter Norvig give a beautiful example in their book Artificial Intelligence: A Modern Approach: rewarding a vacuuming robot for how much dust it
ow it an abstract painting and see what it says. But it does a pretty good job. It works using the same neural-network technology that McCulloch and Pitts imagined in 1943 and lots of us worked on in the early eighties. Back in the 1980s, people successfully did OCR—optical character recognition. They t
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