Epstein Secrets

calm and, before each turn, looks to a screen at the side of the board, reads the instruction, and makes his move. This is the famous match between Garry Kasparov and IBM’s Deep Blue. Kasparov, a child prodigy, became world chess champion at the age of fifteen and, to this day, holds the record for the highest

o a screen at the side of the board, reads the instruction, and makes his move. This is the famous match between Garry Kasparov and IBM’s Deep Blue. Kasparov, a child prodigy, became world chess champion at the age of fifteen and, to this day, holds the record for the highest chess ranking ever achieved. S

ing certain things are true. Science does not forbid beliefs. It just requires you to be prepared to have one overturned if a better one comes along. Richard Feynman summed this up in a lecture he delivered at Cal Tech: “If you want to discover a theorem,” he said, “first, you guess, then you work out some effect

ne 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 way of programming is changing dramatically. After a long hiatus, the power of machine learning has taken off. Much of th

, we programmed computers using algorithms we understood at least in principle. So when machines did amazing things like beating world chess champion Garry Kasparov, we could say that the victorious programs were designed with algorithms based on our own understanding—using, in this instance, the experience and a

hine and founded what may have been the first Al company—Thinking Machines Corporation—to produce and market it. This was despite a lunch he had with Richard Feynman, at which the celebrated physicist remarked, “That is positively the dopiest idea I ever heard.” Maybe “despite” is the wrong word, since Feynman had

ne 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 way of programming is changing dramatically. After a long hiatus, the power of machine learning has taken off. Much of th

, we programmed computers using algorithms we understood at least in principle. So when machines did amazing things like beating world chess champion Garry Kasparov, we could say that the victorious programs were designed with algorithms based on our own understanding—using, in this instance, the experience and a

hine and founded what may have been the first Al company—Thinking Machines Corporation—to produce and market it. This was despite a lunch he had with Richard Feynman, at which the celebrated physicist remarked, “That is positively the dopiest idea I ever heard.” Maybe “despite” is the wrong word, since Feynman had

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 at random and squeake

Afterwords, which were very much on their wavelength. I jumped at the opportunity, the main reason being that the keynote speaker was none other than Richard Feynman. I love 12 HOUSE_OVERSIGHT_016815 to spend time with physicists, the reason being that they think about the universe, 1.e. everything. And no phys

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 at random and squeake

Afterwords, which were very much on their wavelength. I jumped at the opportunity, the main reason being that the keynote speaker was none other than Richard Feynman. I love 12 HOUSE_OVERSIGHT_016232 to spend time with physicists, the reason being that they think about the universe, 1.e. everything. And no phys