Asha Sharma: commitment

Transcript context

…And RL is reinforcement learning? Yes. Yes, exactly. I believe we will see just as much money spent on post-training as we will on pre-training and in the future, more on post-training. We talked a little bit about Nathan Lambert's study where his review was that when a model hits 30 billion parameters, it makes more sense to fine-tune and optimize that 50% of developers according to surveys are now fine-tuning and we know fine-tuning is good, but if you actually go through the full loop, you can get better results. So I think there's a bunch there and I think there's a whole new set of infrastructure and platforms and companies that will be created that are all around this part of the stack. And so I think it's an exciting time to be in the platform space, but it's also an exciting time to be starting companies and be thinking about those problems. I want to make sure people truly understand what you're saying here because not everyone truly understands post-training, pre-training. What's the simplest way to understand the difference there and just why it's such a big deal that investment is moving to post-training?…

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