Dwarkesh Kheterpal

I got a chance to play around with both Orion and also the Meta AI app, and the voice mode was super smooth.

It was quite impressive.

On the point of what the different labs are optimizing for, to Steelman, their view, I think a lot of them think that once you fully automate software engineering and AI research, then you can kick off an intelligence explosion where you have millions of copies of these software engineers replicating the research that happened between Lama 1 and Lama 4.

that scale of improvement, again, in a matter of weeks or months rather than years.

And so it really matters to just close the loop on the software engineer, and then you can be the first to ASI.

What do you make of that?

It's really interesting to me that you basically agree with the premise that there will be an intelligence explosion and something like superintelligence on the other end.

But then if that's the case, tell me if I'm misunderstanding you.

If that's the case, why even bother with personal assistance and whatever?

Why not just get to superhuman intelligence first and then deal with everything else later?

Publicly available data is running out.

So major AI labs like Meta, Google DeepMind, and OpenAI all partner with scale to push the boundaries of what's possible.

Through SCALE's Data Foundry, major labs get access to high-quality data to fuel post-training, including advanced reasoning capabilities.

SCALE's research team, SEAL, is creating the foundations for integrating advanced AI into society through practical AI safety frameworks and public leaderboards around safety and alignment.

Their latest leaderboards include Humanity's Last Exam, Enigma Eval, Multi-Challenge, and Vista, which test a range of capabilities from expert-level reasoning to multimodal puzzle solving to performance on multi-turn conversations.

Scale also just released Scale Evaluation, which helps diagnose model limitations.

Leading frontier model developers rely on Scale Evaluation to improve the reasoning capabilities of their best models.

If you're an AI researcher or engineer and you want to learn more about how Scale's data foundry and research lab can help you go beyond the current frontier of capabilities, go to scale.com slash thwarkash.

So if you buy this view that this is where intelligence is headed,

The reason to be bullish on Meta is obviously that you have all this distribution, which you can also use to learn more things that can be useful for training.