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rol, planning, estimation, learning, and cognitive science. Barely into her thirties herself, she has co-authored a number of papers with her veteran Berkeley colleague and mentor Stuart Russell which address various aspects of machine learning and the knotty problems of value alignment. She shares Stuart’
ces at UC Berkeley. She co-founded and serves on the steering committee for the Berkeley AI Research (BAIR) Lab and is a co-principal investigator in Berkeley’s Center for Human-Compatible AI. George Dyson is a historian of science and technology and the author of Baidarka: the Kayak, Darwin Among the Mach
e and evaluate a vast selection of possible future moves. But the majority of predictions of AI, e.g., robotic maids, turned out to be illusory. When Deep Blue beat Garry Kasparov at chess in 1997, the most 20 HOUSE_OVERSIGHT_016823 powerful room-cleaning robot was a Roomba, which moved around vacuuming a
rol, planning, estimation, learning, and cognitive science. Barely into her thirties herself, she has co-authored a number of papers with her veteran Berkeley colleague and mentor Stuart Russell which address various aspects of machine learning and the knotty problems of value alignment. She shares Stuart’
ces at UC Berkeley. She co-founded and serves on the steering committee for the Berkeley AI Research (BAIR) Lab and is a co-principal investigator in Berkeley’s Center for Human-Compatible AI. George Dyson is a historian of science and technology and the author of Baidarka: the Kayak, Darwin Among the Mach
e and evaluate a vast selection of possible future moves. But the majority of predictions of AI, e.g., robotic maids, turned out to be illusory. When Deep Blue beat Garry Kasparov at chess in 1997, the most 20 HOUSE_OVERSIGHT_016240 powerful room-cleaning robot was a Roomba, which moved around vacuuming a
that she treats them coldly, as if they were mere laboratory animals. They appear to revel in her company, and in the blinking, thrumming toys in her Berkeley lab. For years after her own children had outgrown it, she kept a playpen in her office. Her investigations into just how we learn, and the parallel
Machines were simply faster at doing brute-force calculations, had prodigious amounts of memory, and were not prone to errors. One article described Deep Blue’s victory not as that of a computer, which was just a dumb machine, but as the victory of hundreds of programmers over Kasparov, a single individual.
that she treats them coldly, as if they were mere laboratory animals. They appear to revel in her company, and in the blinking, thrumming toys in her Berkeley lab. For years after her own children had outgrown it, she kept a playpen in her office. Her investigations into just how we learn, and the parallel
Machines were simply faster at doing brute-force calculations, had prodigious amounts of memory, and were not prone to errors. One article described Deep Blue’s victory not as that of a computer, which was just a dumb machine, but as the victory of hundreds of programmers over Kasparov, a single individual.
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