Demis Hassabis, the CEO of Google DeepMind, has said that modern-day large language models (LLMs) are still missing critical capabilities such as long-term planning, continual learning, and better reasoning skills.
While foundational AI models such as Google’s Gemini 3 can process text, images, and video, LLMs still do not understand physics, causality, or how actions affect outcomes over time, according to the Nobel Prize-winning AI researcher. Instead, Hassabis believes in developing ‘world models’ – AI systems can better understand the physics of the world – to fill the gaps that exist today.
“This idea of, like, you know, the system actually understanding better the physics of the world, so that it can run simulations, kind of in its mind to test its own hypotheses. You know, these are things that you know the best scientists do, human scientists do. And so far, our AI systems, you know, are not able to do that,” he said on a recent podcast hosted by CNBC.
“If you really want to understand how the world works, so that maybe you can invent something new in the world, or explain something about the world that was not known before, which is basically what scientific theory does, then you have to have this accurate model of how the world works, starting with intuitive physics and
and how the physics of the world works, but all the way up to biology, you know, and economics,” he further explained.
Hassabis is not alone in betting on world models as the next frontier of AI. Yann LeCun, former chief AI scientist of Meta and famed AI/ML researcher, has also laid out his vision of world models as the future. In December 2025, LeCun announced the launch of his new startup called Advanced Machine Intelligence (AMI) that will be focused on developing world models.
Despite their shared belief in world models, Hassabis and LeCun do not see eye to eye on several issues such as the definition of general intelligence.
LeCun has said that the concept of general intelligence does not exist as it is used to designate human-level intelligence, which is not general but super-specialised. “We think of ourselves as being general, but it’s simply an illusion because all of the problems that we can apprehend are the ones that we can think of,” the Turing Award winner said.
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Responding to his remarks, Hassabis said that LeCun was “plain incorrect” as he was “confusing general intelligence with universal intelligence”. “Brains are the most exquisite and complex phenomena we know of in the universe (so far), and they are in fact extremely general,” Hassabis wrote in a post on X.
