One of the ways you can make models better and more performance is by doing sampling because models are stochastic. You can take a file system, you can fork it a 100 times, run the same prompt with different parameters on these different forks, and then pick the best one.

Every time you run the model, you might get better results, you might get worse results.

34:21 / 34:54

models better and more performance is by doing sampling because models are stochastic. Every time you run the model, you might get better results, you might get worse results. And if there's a way to verify whether the result is good or bad, you can sample from the model. So what we do is because the system is immutable, has this characteristics of being very cheap to fork. So you can take a file system, you can fork it a 100 times, run the same prompt with with different parameters on on these different, forks, and then pick the best one. Do it repeatedly.

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Technical insight that explains how AI performance optimization actually works. The concrete example of forking 100 times provides specific, actionable understanding of AI system architecture.

34:21 - 34:5432sBusiness Mechanics

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