Rob Wiblin

speaker

5,091 appearances 15 recordings 1 series first heard Oct 2021 last heard 6 Aug

Rob Wiblin’s voice in public audio — every appearance, attributed to the second.

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recordings per month · last 12 months

Recordings per month over the last 12 months — 13 in all, peaking in Apr 2026 with 3.

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80,000 Hours Podcast · What the hell happened with AGI timelines in 2026? – Rob Wiblin · 4 Aug 2026 podcast

But it's tough to convince people to spend tens of billions of dollars on something they personally find useless.

So I kind of see that as effectively a dead argument now.

Here's another remarkable, surprising indicator.

On average, over the last 10 years, the cost to buy a given amount of compute has fallen around 30% per year.

Is that continuing now?

No.

In fact, the cost to rent an old AI chip from 2022, the NVIDIA H100, it's going back up.

Since AI agents took off in December, it's risen fully 50%.

So it's now a little higher today than it was two years ago.

That's despite there being obviously many better, more modern chips out there and available compute in the world tripling every year.

The likely reason is that the usefulness of AI models to people is growing even faster than that supply of computer chips.

And that's the case because the machines used to print them are literally the most complex devices humans have ever operated by none.

Which then has the effect that even in the middle of this crazy AI boom, we're only expanding the number of them that exist and are operating by 20% a year.

And that in turn helps to explain why the tech industry as a whole is willing to pay such a premium for chips right now and to spend so much on their data center build out.

The AI sector as a whole, the hyperscalers, they're spending maybe $600 billion on AI capital expenditure investment in 2026.

For that to earn a good return to investors, those data centers will have to bring in about $600 billion in revenue every year because the chips only last for so long.

That is a huge amount, a lot more than they're bringing in today.

But we're seeing signs of why the companies involved are willing to bet so much money on the belief that that will ultimately happen.

Firstly, OpenAI and Anthropic alone are on track to hit an annualized revenue run rate of over $200 billion by the end of the year, so they're getting within striking distance.

In a chip supply crunch, the rental value of the chips they're throwing into those data centers now, that could easily keep going up and up over time rather than down as it did historically.

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