, who designed a commercial Go program called Crazy Stone.1-le had thought computer mastery of the game was a decade away. The IBM chess computer Deep Blue, which famously beat grandmaster Garry Kasparov in 1997, was explicitly programmed to win at the game. But AlphaGo was not preprogrammed to play

e misconceptions. EFTA00690478 how to: TECHNOLOGY EFTA00690479 30.05.2017 Artificial Intelligence and the Game of the Century — Kasparov vs. Deep Blue with Garry Kasparov, Michael Hawley Former World Chess Champion Gary Kasparov talks about where Machine Intelligence ends and Human Creativity be

t can breach the bounds of the rules of the game. Given that, either brute force or ML/statistical approaches works well enough to build things like Deep Blue or the Google self-driving car. At Palantir (where I work), we have, to date, stayed away from heavy machine learning or algorithmic approaches to

search firm. EFTA00696551 Gr how to: SCIENCE WEEK EFTA00696552 30.05.2017 Artificial Intelligence and the Game of the Century — Kasparov vs. Deep Blue with Garry Kasparov, Michael Hawley Former World Chess Champion Gary Kasparov talks about where Machine Intelligence ends and Human Creativity be

From: How To Academy To:j <[email protected]> Subject: Artificial Intelligence and the Game of the Century — Kasparov vs. Deep Blue: with Gany Kasparov & Michael Hawley Date: Thu, 02 Mar 2017 10:06:00 +0000 Artificial Intelligence & the Game of the Century EFTA00669449 how t

t can breach the bounds of the rules of the game. Given that, either brute force or ML/statistical approaches works well enough to build things like Deep Blue or the Google self-driving car. At Palantir (where I work), we have, to date, stayed away from heavy machine learning or algorithmic approaches to

t can breach the bounds of the rules of the game. Given that, either brute force or ML/statistical approaches works well enough to build things like Deep Blue or the Google self-driving car. At Palantir (where I work), we have, to date, stayed away from heavy machine learning or algorithmic approaches to

t can breach the bounds of the rules of the game. Given that, either brute force or ML/statistical approaches works well enough to build things like Deep Blue or the Google self-driving car. At Palantir (where I work), we have, to date, stayed away from heavy machine learning or algorithmic approaches to

competition because of pancreatic cancer.) Chinook had no machine learned aspects. EFTA_R1_02074941 EFTA02702510 In 1997, Garry Kasparov lost to Deep Blue at chess—Kasp- arov was the reigning world chess champion. In one pivotal game Kasparov remarked on the "superior intelligence" of the machine duri

tch?v=4fjmnOQuqao 340M people watched the video of the match. Key thing is that AlphaGo is creative and intuitive. It doesn't =se calculations like Deep Blue but gets to symbolic reason through =einforced learning on neural networks. -Joi > On Apr 23, 2016, at 9:35 AM, jeffrey E. <[email protected]>

v=4fjmnOQuqao > 340M people watched the video of the match. > Key thing is that AlphaGo is creative and intuitive. It doesn't =se calculations like Deep Blue but gets to symbolic reason through =einforced learning on neural networks. > - Joi » On Apr 23, 2016, at 9:35 AM, jeffrey E. <[email protected]

day, holds the record for the highest chess ranking ever achieved. Some consider him one of the most intelligent people on the planet. His opponent, Deep Blue, is a massively parallel chess-playing computer built by IBM’s Watson Research Laboratory. The machine itself sits a few blocks north of the tourname

creators were limiting what it had been asked to do. At which point the AI would turn to thinking about how to escape those bounds. It would be like Deep Blue programmed to plan its own prison break. And as much as humans might try to stifle a smart machine, we’d be fighting to contain something more powerf

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

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.

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

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.