Google’s DeepMind CEO exposes the shocking flaw holding AI back from full AGI - here are the details

Even though AI can solve world-class math problems, it still struggles with high school-level equations. That's the paradox that Google DeepMind CEO Demis Hassabis claims is preventing AI from becoming fully AGI. The culprit is apparently an unexpected lack of consistency.

Demis Hassabis believes that the most significant barrier to full AGI is AI's inconsistency in reasoning and problem-solving. Fixing the flaw will necessitate advances in reasoning, planning, and memory, not just more data or computing power.

What does “jagged intelligence” mean in AI?

Demis Hassabis stated that "some missing capabilities in reasoning and planning in memory" need to be fixed. Hassabis stated in a Tuesday episode of the "Google for Developers" podcast that even sophisticated models such as Google's Gemini still make mistakes on problems that most schoolchildren could figure out, as quoted in a report by Business Insider.


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“It shouldn't be that easy for the average person to just find a trivial flaw in the system," he stated.

He cited Gemini models that have been improved with DeepThink, a method that improves reasoning, and that have the potential to take home gold at the International Mathematical Olympiad, the most prominent math competition in the world.

The same systems, he claimed, can "still make simple mistakes in high school maths," and he referred to them as "uneven intelligences" or "jagged intelligences,” as quoted in a report by Business Insider.

"Some dimensions, they're really good; other dimensions, their weaknesses can be exposed quite easily," he stated.

Why is it so important for AGI to be consistent?

It's not just about getting more data and computing power to get to Artificial General Intelligence (AGI), which is the point at which AI can think and reason like a person in all areas. Hassabis thinks that the missing piece is to make reasoning, planning, and memory better, as quoted in a report by Business Insider.

AI's weaknesses can make its strengths less useful if they aren't consistent. For example, an AI that can solve graduate-level physics problems but not basic algebra is not really intelligent in the same way that people are. Google CEO Sundar Pichai came up with the term "AJI", Artificial Jagged Intelligence, to describe the current state of the technology because it isn't balanced, as quoted in a report by Business Insider.

Hassabis says the industry needs "new, harder benchmarks" to thoroughly test AI's strengths and weaknesses and make sure it works well on all kinds of tasks.

How far away are we from getting real AGI?

Demis Hassabis is still hopeful, though, and thinks that AGI could be here in five to ten years. He does, however, stress that Big Tech still hasn't figured it out.

Before the launch of GPT-5, OpenAI CEO Sam Altman said something similar. He said that GPT-5 is a big step forward, but it is not yet true AGI. Altman said that one major gap is that AI can't keep learning on its own from new information it comes across in real time.


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Both leaders agree that the next big steps forward in AI won't just come from bigger models. They will also come from smarter models that have the kind of balanced, adaptable intelligence that people take for granted.

FAQs

What is preventing AI from achieving AGI?
AI lacks consistency, excelling at complex tasks while failing at simpler ones.

How would Demis Hassabis describe current AI?
He refers to it as "jagged intelligence" because it is strong in some areas but weak in others.