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

ans think creatively, computers do not. * ‘The process of understanding and communication is complex, much more complex than the digital theorems of Claude Shannon and Harry Nyquist. « Understanding is hard. « The communication of understanding is even harder. HOUSE_OVERSIGHT_015687 CONTENTS Preface

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

, “A Scientist Rebels,” Zhe Atlantic Monthly, January 1947. 31 Warren Weaver, “Recent Contributions to the Mathematical Theory of Communication,” in Claude Shannon & Warren Weaver, The Mathematical Theory of Communication (Urbana, IL: University of Illinois Press, 1949), p. 8 (emphasis in original). Shan

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

, “A Scientist Rebels,” Zhe Atlantic Monthly, January 1947. 31 Warren Weaver, “Recent Contributions to the Mathematical Theory of Communication,” in Claude Shannon & Warren Weaver, The Mathematical Theory of Communication (Urbana, IL: University of Illinois Press, 1949), p. 8 (emphasis in original). Shan

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

n Turing wondered what it would take for machines to become intelligent. John von Neumann wondered what it would take for machines to self-reproduce. Claude Shannon wondered what it would take for machines to communicate reliably, no matter how much noise intervened. Norbert Wiener wondered how long it wo

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

n Turing wondered what it would take for machines to become intelligent. John von Neumann wondered what it would take for machines to self-reproduce. Claude Shannon wondered what it would take for machines to communicate reliably, no matter how much noise intervened. Norbert Wiener wondered how long it wo