Demis Hassabis

speaker

292 appearances 1 recordings 1 series first heard Apr 2026 last heard 7 Apr

Demis Hassabis’s voice in public audio — every appearance, attributed to the second.

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Recordings per month over the last 12 months — 1 in all, peaking in Apr 2026 with 1.

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The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch · 20VC: DeepMind's Demis Hassabis on Why AGI is Bigger than the Industrial Revolution | Why LLMs Will Not Commoditise & We Have Not Hit Scaling Laws | Bottlenecks in AI & The Energy Crisis Caused By AI | Whether AI Will Do More to Harm or Help Inequality · 7 Apr 2026 podcast

I think compute is the big one, not just for the obvious reason of scaling up your ideas and your systems as the scaling laws, as they're called, keeping on building bigger and bigger architectures with more and more parameters.

And as you do that, you get more intelligent systems.

But the other thing you need a lot of compute for is for doing experiments.

The computers, the cloud is our workbench, basically.

So if you have a new idea, a new algorithmic idea, but you want to test it, you kind of got to test it at a reasonable scale.

Otherwise, it won't hold when you actually put it into the main system.

So you need quite a lot of compute if you have a lot of researchers with lots of new ideas.

Do you think that's true?

No, I don't think so.

I think it's a bit more nuanced than that.

So, of course, when the leading companies all started building these large language models, you're getting enormous jumps with each generation of new system.

You know, maybe they're almost like doubling in performance.

At some point that had to slow down.

So it's not kind of continuing to be exponential, but that doesn't mean there isn't great returns.

still for scaling the existing systems up further.

So we and the other frontier labs are getting a lot of great returns on that kind of compute expansion.

So I would say the returns are kind of still very substantial, although they're a bit less than they were obviously at the start of all of this scaling.

I think actually in most areas we are ahead of where I thought we would be.

If you think about things like the video models or even now with our newer systems like Genie, they're interactive world models, which I think is kind of incredible if you sort of step back and think about it.

I think if you'd shown me that five, 10 years ago, I would have been pretty amazed.

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