Google’s AlphaGo Artificial Intelligence program has outdone itself. If in 2016 he surprised us by defeating the best human players of the ancient Chinese board game ‘Go’ – in which he prizes intuition to win -, he now presents himself with a totally self-taught new version: he is smarter than ever and he has learned in three days what humanity has cost thousands of years and, moreover, without any human help.
And the updated version of AlphaGo is completely self-taught, an important step towards the emergence of machines that achieve superhuman capabilities “without human input,” according to the program’s authors in the journal Nature.
The ‘Go’ game is the most complex challenge for two people that have ever been invented and Alphago Zero has mastered it in three days. He created his own new movements to eclipse all the knowledge that we have so much difficulty obtaining. Finally, AlphaGo Zero won by 100 games to 0, winning overwhelmingly.
“AlphaGo Zero not only rediscovered the common patterns and openings that humans tend to play … it finally discarded them, preferring their own variants that humans do not even know or play at the moment,” said David Silver, principal investigator at Alpha Go .
Zero’s predecessor, AlphaGo, was incredible, but the new self-taught version has redefined his training arsenal by completely eradicating the human teachings of his education. He took the rules of the game and, without instructions; the system learned how to play, devised a strategy and improved as it competed against itself, starting with a “completely random game” to discover how the reward was won.
Unlike its predecessors, AlphaGo Zero “is no longer limited by the limits of human knowledge,” Silver and DeepMind CEO Demis Hassabis wrote in a blog post.
In the study, researchers expose how that surprising self-sufficiency has ‘sharpened’ Zero’s intelligence to become devastating: in 100 games there was not a single victory to the contrary. Not even one.
Even more surprising, that trick came after only three days of AlphaGo Zero self-game training, in which it distilled the equivalent of thousands of years of human knowledge of the game.
Aside from being self-taught, the team behind AlphaGo Zero attributes its Go domain to a unique enhanced neural network (as if it were a human brain) and more advanced training simulations.
In comparison, AlphaGo Zero had four data processing units and AlphaGo 48; AlphaGo Zero played 4.9 million training games for three days and AlphaGo 30 million games over several months.
But just because AI is advancing at such an amazing rate does not necessarily mean that Zero is smarter or more capable of humans in other fields away from this complicated board game invented more than 2,500 years ago.
“However, this is not the beginning of any end because AlphaGo Zero, like all other successful AIs so far, is extremely limited in what it knows and what it can do compared to humans and even other animals,” he said. Clarified Satinder Singh of the University of Michigan (USA).
They may not be able to do everything humans can do right now, but they can do so many other things that we can not… welcome to the future.