While it's been possible to develop systems that can break down problems and complete tasks autonomously in the realm of games — such as the complex strategy board game Go — bringing such a technology into the real world is proving harder.
"The question is, how fast can we generalize the planning ideas and agentic kind of behaviors, planning and reasoning, and then generalize that over to working in the real world, on top of things like world models — models that are able to understand the world around us," Hassabis said."
"And I think we've made good progress with the world models over the last couple of years," he added. "So now the question is, what's the best way to combine that with these planning algorithms?"