Charlie O'Neill

speaker

259 appearances 2 recordings 1 series first heard Jul 2026 last heard 15 Sep

Charlie O'Neill’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 — 2 in all, peaking in Sep 2026 with 1.

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Prof G Markets · Gas Is Back Above $4 — And Could Keep Rising · 21 Jul 2026 podcast

And so now it's much more about, okay, we're really seeing under the hood that the reason that anthropic and open AI models are so expensive is because they have great margins.

Because they were sitting at the frontier and there was no real competitor at the very frontier.

And again, a lot of this stuff, it is inelastic.

You do demand frontier intelligence.

But now we're really seeing, okay, if we do have multi-trillion parameter open source models that any company can host on their own GPUs and can post-train and then host on their own GPUs,

Then what that's telling us and a lot of analysis is telling us is that the frontier labs margins are just massive.

And so I think that the shift that's going to happen now is if there is an alternative that is essentially the same and to 99.99% of people doing 99.99% of things is indistinguishable.

like Kimi is indistinguishable from a Fable or a GPD 5.6 Sol, we're just going to see those margins shift.

So instead of being 80% to the person who trained the model, they might end up being 40%, and the rest of that margin is going to be distributed, one, to the consumer, and then two, to the rest of the ecosystem.

So the compute providers and the inference providers are going to be big wins of all this competition amongst consumers.

you know, model trainers.

It's no longer the case where there's only one or two players who can do this and capture those massive margins.

There's going to be much lower margins for model trainers and the rest is going to kind of be spread out amongst the ecosystem.

I've obviously been a big advocate and proponent of open source for a long time and want open source to win in some reasonably significant capacity.

I think my honest take here is that this isn't the death knell for anthropic open AI.

I think ideally and probably most likely now we're going to live in a world where there are a few key core frontier players and then a large diverse ecosystem of open source model providers.

The reason I think that is because of

the distribution of tasks in the economy that we're currently trying to tackle with LLMs and the distribution of tasks in the economy that we should be tackling with LLMs in the next 10 years.

I think what we're going to see is a little bit of a bifurcation.

I think tasks that we can currently conceive of as being economically useful,

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