Vibhu (Vibhu?)

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157 appearances 1 recordings 1 series first heard Jul 2026 last heard 23 Jul

Vibhu (Vibhu?)’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 Jul 2026 with 1.

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What else do people not see in starting a foundation model?

You know, there's a lot of compute.

There's a lot of capital required, a lot of compute.

You lay out model factory and how to do the training, but there's a lot there, right?

It seems like a never-ending, okay, I want instruction manual for this table, right?

Am I going to environment out building furniture?

Or are we just going to tail end?

Like, we need some general solution.

The analogy people draw often is the RL phase is where you don't learn as much new knowledge.

You reshift.

So, you know, you reshift distribution and you can have it reasoned towards what you want.

On your point about mid-training, a lot of mid-training is still just continue pre-training in a domain, say medicine, then you do RL.

So still just pre-training.

It's also a thing people take bets on, right?

When you say more Neolabs, you're doing a version of, we'll do foundation models, scale them up, next token predictors.

A lot of other Neolabs that we see want to take a completely different approach, right?

At some level, you're right.

It's all compute efficiency and that's the net objective.

But, you know, some are, okay,

Different architecture, like vastly different amounts of compute spend.

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