Dwarkesh Patel

There's a question going forward.

So right now we have models that have this distinction between training and inference and one could argue that there's like a smaller and smaller difference between the different models.

Going forward, if you're really expecting something like human level intelligence,

humans learn on the job.

You know, if you think about your last 30 years, what makes Satya Token so valuable?

It's the last 30 years of wisdom and experience you've gained at Microsoft.

And we will eventually have models if they get to human level, which will have this ability to continuously learn on the job.

And that will drive so much value to the model company that is ahead, at least in my view, because you have copies of one model broadly deployed through the economy, learning how to do every single job.

And unlike humans, they can amalgamate their learnings to that model.

So there's this sort of

continuous learning sort of exponential feedback loop, which almost looks like a sort of intelligence explosion.

If that happens and Microsoft isn't the leading model company by that time, doesn't then this, you know, you're saying, well, we substitute one model for another, et cetera, matter less because they're just like this one model knows how to do every single job in the economy.

The other long tail don't.

So according to Dylan's numbers, there's going to be half a trillion in AI capex next year alone, and labs are already spending billions of dollars to snag top researcher talent.

But none of that matters if there's not enough high-quality data to train on.

Without the right data, even the most advanced infrastructure and world-class talent won't translate into end value for the user.

That's where LibriVox comes in.

LibriVox produces high-quality data at massive scale, powering any capability that you want your model to have.

It doesn't matter whether you need a coding agent that needs detailed feedback on multi-hour trajectories, or a robotics model that needs thousands of samples on everyday tasks, or a voice agent that can also perform real-world actions for the user, like booking them a flight.

To be clear, this isn't just off-the-shelf data.