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A Gamut of Games

AI Magazine

In 1950, Claude Shannon published his seminal work on how to program a computer to play chess. Since then, developing game-playing programs that can compete with (and even exceed) the abilities of the human world champions has been a long-sought-after goal of the AI research community. In Shannon's time, it would have seemed unlikely that only a scant 50 years would be needed to develop programs that play world-class backgammon, checkers, chess, Othello, and Scrabble. These remarkable achievements are the result of a better understanding of the problems being solved, major algorithmic insights, and tremendous advances in hardware technology. Computer games research is one of the important success stories of AI. This article reviews the past successes, current projects, and future research directions for AI using computer games as a research test bed.


The Three Breakthroughs That Have Finally Unleashed AI on the World

#artificialintelligence

A few months ago I made the trek to the sylvan campus of the IBM research labs in Yorktown Heights, New York, to catch an early glimpse of the fast-arriving, long-overdue future of artificial intelligence. This was the home of Watson, the electronic genius that conquered Jeopardy! in 2011. The original Watson is still here--it's about the size of a bedroom, with 10 upright, refrigerator-shaped machines forming the four walls. The tiny interior cavity gives technicians access to the jumble of wires and cables on the machines' backs. It is surprisingly warm inside, as if the cluster were alive. Today's Watson is very different. It no longer exists solely within a wall of cabinets but is spread across a cloud of open-standard servers that run several hundred "instances" of the AI at once. Like all things cloudy, Watson is served to simultaneous customers anywhere in the world, who can access it using their phones, their desktops, or their own data servers.


The Three Breakthroughs That Have Finally Unleashed AI on the World

#artificialintelligence

A few months ago I made the trek to the sylvan campus of the IBM research labs in Yorktown Heights, New York, to catch an early glimpse of the fast-arriving, long-overdue future of artificial intelligence. This was the home of Watson, the electronic genius that conquered Jeopardy! in 2011. The original Watson is still here--it's about the size of a bedroom, with 10 upright, refrigerator-shaped machines forming the four walls. The tiny interior cavity gives technicians access to the jumble of wires and cables on the machines' backs. It is surprisingly warm inside, as if the cluster were alive. Today's Watson is very different. It no longer exists solely within a wall of cabinets but is spread across a cloud of open-standard servers that run several hundred "instances" of the AI at once.


AlphaGo Zero Goes From Rank Beginner to Grandmaster in Three Days--Without Any Help

IEEE Spectrum Robotics

In the 1970 sci-fi thriller Colossus: The Forbin Project, a computer designed to control the United States' nuclear weapons is switched on, and immediately discovers the existence of a Soviet counterpart.


Surprise: AI In 2019

#artificialintelligence

A long time ago in an innovation ecosystem far, far away… a recent MIT graduate started his career in a vintage 1970's Massachusetts Route 128 Artificial Intelligence (AI) startup doing speech recognition, re-named Verbex after Exxon acquired the company. Fast forward to AI in 2019, and what stands out most to that grad (me) are two pleasant surprises. The first surprise is the degree to which highly competitive IT businesses have embraced open source AI. Google's TensorFlow has over 120,000 stars on GitHub, which the largest home of open source code communities, and Microsoft acquired GitHub in 2018. Facebook's PyTorch is also quite popular, especially in academic and industrial research communities, with over 25,000 stars on GitHub.