Monday, August 20, 2018
Submit your own News for
inclusion in our Site.
Click here...
Breaking News
Logitech Goes Vertical With Advanced Ergonomic Mouse
Xpanded LG XBOOM Audio lineup takes Stage at IFA 2018
Amazon to Release Live TV Recorder
U.S. Wants to Wiretap Facebook Messenger, Report Says
More Affordable, 13-inch MacBook and $160 AirPower Expected at Apple's Event
Google to Launch Its Own Smart Display, Report Says
Nvidia Reports Record Revenue From Datacenter, Gaming, Professional Visualization, Automotive
Arm Client CPU Roadmap Includes Advanced Hercules and Deimos Chips
Active Discussions
Which of these DVD media are the best, most durable?
How to back up a PS2 DL game
Copy a protected DVD?
roxio issues with xp pro
Help make DVDInfoPro better with dvdinfomantis!!!
menu making
Optiarc AD-7260S review
cdrw trouble
 Home > News > General Computing > Google'...
Last 7 Days News : SU MO TU WE TH FR SA All News

Thursday, December 07, 2017
Google's AlphaZero Masters Chess Within Hours

Google's AlphaZero, a computer algorithm running on Google's AI-specific Tensorflow processing units, has managed to learn, master and then dominate the game of chess in just four hours.

Google's DeepMind AI offspring, AlphaZero, took four hours to teach itself how to play chess and then proceeded to demolish the best, highest rated chess computer, Stockfish. After 100 games, AlphaZero racked up 28 wins and zero losses.

Chess can be incredibly complex, with possible position totals that exceed 10100 possibilities.

Google's algorithm used self-play reinforcement learning, starting at a chess rating of ten and took 700,000 iterative training steps over four hours before taking on Stockfish. During its training phase, the algorithm had no access to opening books or endgame tables. It simply played a large number of iterative games against itself.

This training session ran on 5,000 first-generation Google Tensorflow Processing Units (TPUs) to generate the self-played games. It also used 64 second-generation TPUs to train the neural networks for those games. During the match, AlphaZero ran on a single machine with four TPUs. Stockfish ran on a single machine with 64 threads and a hash size of 1GB.

During a multiple-game tournament, both algorithms were given one minute per move. During play, Stockfish searched 70 million positions per second, while AlphaZero searched only 80,000 in the same time period.

The full result of the 100 game match gave AlphaZero 28 wins and zero losses, but 72 draws. Of those 28 wins, 25 came as white and only three as black.

We should notice here that AlphaZero made up its own opening book, meaning Stockfish could not make use of its considerable opening preparation.

Google estimates that each TPU is capable of delivering up to 225,000 predictions per second. A regular old CPU can muster just over 5,000.

Messenger Games Get Support for Live Streaming and Video Chats        All News        HTC Opens Pre-orders for Vive Focus VR
YouTube Said to Launch Music Subscription Service     General Computing News      HTC Opens Pre-orders for Vive Focus VR

Get RSS feed Easy Print E-Mail this Message

Related News
Google's AlphaGo Wins Chinese Go Master in First Round

Most Popular News
Home | News | All News | Reviews | Articles | Guides | Download | Expert Area | Forum | Site Info
Site best viewed at 1024x768+ - CDRINFO.COM 1998-2018 - All rights reserved -
Privacy policy - Contact Us .