Finally, a big name has the courage to tell it: we are nowhere near AGI.

Demis Hassabis, CEO of Google DeepMind and Nobel laureate for AlphaFold, put it neat and clear:

"Today's systems are nowhere near [AGI]. Doesn't matter how many Erdős problems you solve… I think it's far, far from what a true invention, or someone like Ramanujan, would have been able to do."

This is the elephant in the room that many AI enthusiasts prefer not to see, or are actively trying to hide.

Erdős problems are well defined, often combinatorial, on finite spaces. They are exactly the kind of problems on which current AI can achieve spectacular performance with a lot of compute and knowledge.

A neural network can search a huge graph of possibilities. It can recombine existing knowledge at unprecedented scale. It can discover surprising solutions inside an already defined conceptual space.

But true invention is something else.

True invention is not only solving a problem.

It is inventing new objects, new dimensions, new connections. It is inventing new problems.

From resolving to inventing there is a discontinuity that we don't know how to bridge.

We are making extraordinary tools.
But we are nowhere close to AGI.

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