In AI model development, compute has proven to be the most critical resource for scaling model capabilities, as demonstrated by the current compute shortage in the industry where practitioners simply throw more compute at problems to achieve better performance.
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The AI Scaling Debate Is Over. Compute Won Every Time.Añadido:
There is this calculation that came out of Open AI. Essentially, it's this idea that is if you have data, compute, and parameters, you can linearly extend the capabilities of a model as much as you just keep on adding on to it. There's some people who pushed back and said, like, "Well, data is most important."
Those people quickly lost. And then there's some people who said, "Well, no, you know, parameter is more important."
Those people also have been to loss over time. Compute has still remained that important thing where we're seeing it now. We have a compute shortage happening right now. Where people go like, "Okay, just throw more compute at it."
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