Deep Blue

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Deep Blue

A super computer developed by researchers at IBM to explore the use of parallel processing to solve complex computing problems. It is known as the first computer to beat the current chess World Grand Master.

Deep Blue started it's life as a PhD project at Carnegie Mellon University by PhD students Feng-hsiung Hsu and Murray Campbell. Chiptest, as it was known then, consisted of a custom designed chip hosted in a Sun 3/160 computer.

The project moved over to IBM in 1989 when Hsu and Campbell joined IBM. Deep Thought, as it was known by then, played for the first time against Garry Kasparov in the same year. The game of two matches was easily won by Kasparov.

The next match against Kasparov took place in February 1996. By then the machine was again renamed, at that time it was known as Deep Blue. It was also heavily re-engineered: it was by then running on a 32-node RS/6000 cluster, each containing 8 custom designed chips. Alas, Kasparov won again.

The breakthrough finally happened in February 1997: with both the algorithm and the raw speed significantly improved, Deep Blue beat Kasparov 3.5:2.5.


Deep Blue

The first computer to beat a human chess master. In 1996, IBM's Deep Blue beat Garry Kasparov in game one of a six-game match and won the entire rematch a year later.

From ChipTest to Deep Thought to Deep Blue
Deep Blue originated as the ChipTest chess-playing computer at Carnegie Mellon University in the mid-1980s. Evolving into Deep Thought under IBM's direction, it won the North American and World Class Chess Championships in the late 1980s.

Specialized for Chess
Deep Blue was based on a 30-node RS/6000 parallel computer running AIX (IBM's Unix). With each node augmented by 480 chips specialized for the game, Deep Blue could evaluate up to 20 chess moves ahead. See RS/6000 and Watson.
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Michigan: School of Information, University of Michigan, 2007 <https:// deepblue.
Rather than find the best moves through sheer computational force the way IBM's DeepBlue did to beat chess champion Gary Kasparov, AlphaGo's approach is based on convolutional neural networks and reinforcement learning, allowing it to essentially teach itself over time.
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Finally, the Jeopardy Challenge represents a unique and compelling AI question similar to the one underlying DeepBlue (Hsu 2002)--can a computer system be designed to compete against the best humans at a task thought to require high levels of human intelligence, and if so, what kind of technology, algorithms, and engineering is required?
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