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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
rate of knowledge accumulation. John von Neumann also has a cameo in Zhe Human Use of Human Beings, for game theory. What Wiener missed here was von Neumann’s seminal role in digitizing computation. Whereas analog communication degraded with distance, analog computing (like the Differential Analyzer) degr
inging the programmability of bits to the world of atoms. By digitizing not just designs but the construction of materials, the same lessons that von Neumann and Shannon taught us apply to exponentially increasing fabricational complexity. I’ve defined digital materials to be those constructed from a disc
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
rate of knowledge accumulation. John von Neumann also has a cameo in Zhe Human Use of Human Beings, for game theory. What Wiener missed here was von Neumann’s seminal role in digitizing computation. Whereas analog communication degraded with distance, analog computing (like the Differential Analyzer) degr
inging the programmability of bits to the world of atoms. By digitizing not just designs but the construction of materials, the same lessons that von Neumann and Shannon taught us apply to exponentially increasing fabricational complexity. I’ve defined digital materials to be those constructed from a disc
, Steve 47, 68, 296-297, 297, 306 joke 93 world’s funniest 94 Joke Analysis and Production Engine 310 Jones, JP 251 K Kahn, Philip 237 Kamailio 265 Kasparov, Garry 5, 34 and Deep Blue 4-6 Kelvin, Lord 180 Kerr Metric 280 Khayyam, Omar 371 King’s College 17, 211 Kish, Daniel 13 knitting 117 knowledge 8 a
en Think, Learn and Grow in the Early Years. Hamlyn, 2010. ———. The Naked Ape: A Zoologist’s Study of the Human Animal. New edition. Vintage, 2005. Neumann, John Von. The Computer and the Brain. 2nd Revised edition. Yale University Press, 2000. Penrose, Roger. The Large, the Small and the Human Mind. Ne
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
r machine, now known as a Universal Turing Machine, an arbitrary set of computing instructions could be encoded on that same tape. In the 1940s, von Neumann developed an abstract self-reproducing machine called a cellular automaton. In this case it occupied a finite subset of an infinite two- dimensional
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
r machine, now known as a Universal Turing Machine, an arbitrary set of computing instructions could be encoded on that same tape. In the 1940s, von Neumann developed an abstract self-reproducing machine called a cellular automaton. In this case it occupied a finite subset of an infinite two- dimensional
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