DeepMind’s latest AI program can attain “superhuman performance” in tasks without needing to be given the rules.

Like the research hub’s earlier artificial intelligence agents, MuZero achieved mastery in dozens of old Atari video games, chess, and the Asian board games of Go and Shogi.

But unlike its predecessors, it had to work out their rules for itself.

It is already being put to practical use to find a new way to encode videos, which could slash YouTube’s costs.

“The real world is messy and complicated, and no-one gives us a rulebook for how it works,” DeepMind’s principal research scientist David Silver told the BBC.

“Yet humans are able formulate plans and strategies about what to do next.

“For the first time, we actually have a system which is able to build its own understanding of how the world works, and use that understanding to do this kind of sophisticated look-ahead planning that you’ve previously seen for games like chess.

“[It] can start from nothing, and just through trial and error both discover the rules of the world and use those rules to achieve kind of superhuman performance.”

Wendy Hall, professor of computer science at the University of Southampton and a member of the government’s AI council, said the work marked a “significant step forward”, but raised concerns.

“The results of DeepMind’s work are quite astounding and I marvel at what they are going to be able to achieve in the future given the resources they have available to them,” she said.

“My worry is that whilst constantly striving to improve the performance of their algorithms and apply the results for the benefit of society, the teams at DeepMind are not putting as much effort into thinking through potential unintended consequences of their work.

“I doubt the inventors of the jet engine were thinking about global pollution when they were working on their inventions. We must get that balance right in the development of AI technology.”