How long did it take to develop AlphaGo?
After 40 days of self training, AlphaGo Zero became even stronger, outperforming the version of AlphaGo known as “Master”, which has defeated the world’s best players and world number one Ke Jie.
Why was AlphaGo able to play Go so well?
It used a revolutionary new algorithm — one that relied not on previous brute-force algorithms like Minimax but one that sought to replicate the intuition of the masters with powerful reinforcement learning methods. In the end, AlphaGo Zero’s only worthy match was itself… so it learned by playing against itself.
How much does it cost to make AlphaGo Zero?
DeepMind submitted its initial findings in a paper to Nature in April 2017, which was then published in October 2017. The hardware cost for a single AlphaGo Zero system in 2017, including the four TPUs, has been quoted as around $25 million.
Is there an open source version of AlphaGo?
Nochi is open source on GitHub, and still just a tiny Python program that anyone can learn from. Several other efforts to replicate the success of AlphaGo Zero are now underway — e.g. Leela Zero and Odin Zero. After all, the world still needs a super-human Go playing software that anyone can install and learn from!
How much does a Nvidia AlphaZero cost?
More interesting, though, is that AlphaZero (AlphaGo Zero’s successor) only required 40,000 TPU-hours to reach the same level of performance. So if a regular person bought an Nvidia RTX 2060 and ran it for 4.56 years, they could achieve the same result for only $1,151.
What did David Silver do with AlphaGo Zero?
David Silver, one of the first authors of DeepMind’s papers published in Nature on AlphaGo, said that it is possible to have generalised AI algorithms by removing the need to learn from humans. Google later developed AlphaZero, a generalized version of AlphaGo Zero that could play chess and Shōgi in addition to Go.