AlphaGo has built up its acquaintance by studying older matches and playing thousands of games against itself. The company says the ensuing plan is to assign its coloured intelligence “in areas of medicine and science”. Prof Noel Sharkey, a computer scientist at Sheffield University, said it is still a long way from creating a general intelligence.
“It is an incredible acquisition and most experts thought an AI winning at Go was 20 years away so DeepMind is leading the field but this AI doesn’t have general intelligence. It doesn’t know that is playing a game and it can’t make you a cup of tea afterwards.”
Prof Nello Cristianini, from Bristol University, added: “This is machine learning in action and it proves that machines are very capable but it is not general intelligence. No-one has built that yet.”
The types of intelligence exhibited by machines that are good at playing games are seen as very narrow. While they may array algorithms that are advisable in other fields, few think they are close to the all-purpose problem accomplishment abilities of humans that can come up with good solutions to almost any problem they encounter.
Prof Cristianini added that while competition at a gaming level is fine, it should not administer how we view our relationship with apprehensive machines going forward. “We should focus on the good things that we can get out of them and be careful not to create situations in which we put ourselves in advocate competition with machines.”
Both experts agreed that such algorithms could be adjusted to other fields, such as healthcare.
DeepMind has already begun working with the UK’s national health service to acquire apps and other tools for diagnosis.