DeepMind: CEO Demis Hassabis says AGI Lags Human Reasoning

Despite major strides in AI, Demis Hassabis, CEO of DeepMind, cautioned during the AI summit in New Delhi that artificial general intelligence (AGI) is still some way off from replicating human-level reasoning.

While today’s models can perform extraordinary feats, Demis noted that current AI remains constrained in three critical areas: continuous learning, long-term strategic planning and consistency across multiple tasks.

AGI refers to a form of machine learning capable of reasoning and problem-solving in unfamiliar contexts – those it has not been explicitly trained for.

When asked whether AI had reached human-level intelligence, Demis answered: "I don't think we are there yet."

He underscored that the greatest challenge lies in enabling systems to learn continually.

He illustrated the gap between human and AI creativity with an example drawn from theoretical physics: "One way we maybe would test that is you could imagine training a foundation model with a knowledge cutoff of something like 1911 and then see if it could come up with general relativity like Einstein did in 1915.

"But that would be a good test for AGI and I think today's systems clearly would not be capable of doing that."

Long-term planning and consistency across tasks

Demis noted that AI models remain limited to short-term planning horizons.

"They can plan over the short term, but over the long term, the way that we can play over years, they don't really have that capability at the moment," he says.

While current systems can solve immediate problems effectively, they lack the ability to project strategies over months or years, Hassabis says – a core component of human intelligence.

Demis outlined that another major gap is inconsistency.

He says: "So, for example, today's systems can get gold medals in the International Math Olympiad, really hard problems, but sometimes can still make mistakes on elementary maths if you pose the question in a certain way.

"A true general intelligence system shouldn't have that kind of jaggedness."

AI as a co-researcher

Demis sees AGI first acting as a tool to augment human research.

He predicts a "new golden era for scientific discovery" in the coming decade.

"The next phase is going to be incredible for human experts and scientists," he said, adding that "having a tool like AI will really help scientists learn about and be able to understand and process all of that information from multiple different domains".

He described how general AI systems like Google Gemini would collaborate with specialised models like AlphaFold: "If Gemini wanted to or needed to understand the structure of a protein, I think it would be better for it to call AlphaFold as a tool than put all that protein information into the main system."

Demis also discussed risks.

Apart from possible misuse by individuals or nations, he highlighted technical and societal challenges: "There's a societal challenge that may actually end up being the harder problem than the technical ones."

Near-term concerns include cyber and biosecurity risks, alongside the need for international standards on safe AI deployment, Demis outlined.

Despite these hurdles, he remains cautiously optimistic about AGI's trajectory.

"I would say cautious optimism, if the best minds work towards that, I think we'll solve the technical risks," he said.

He further emphasised AI's global potential: "The generation that grows up native with that technology will end up doing some sort of incredible things that we can only dream of right now."

While AGI has not yet achieved human-level intelligence, Demis' comments highlight both AI's promise in enhancing human capabilities and the need for prudent risk management.