3min chapter

80,000 Hours Podcast cover image

#150 – Tom Davidson on how quickly AI could transform the world

80,000 Hours Podcast

CHAPTER

How Much Compute Do You Need to Train AI?

The amount of compute is another way of saying how many calculations did you need to do it? Got it. So maybe in 2020, you'd have needed 10 to the 30 flop to train AGI. But maybe by 2025, your algorithms are 10 times better. And so you only need 10 to the 29 flop to training AGI. The basic dynamic in this framework is that in each year, our algorithm has improved somewhat and we decide to use more compute in a training run than we had done in the previous year. Because it's profitable, et cetera. Exactly. Let's say we use twice as much compute as the previous year and our algorithms are twice as good

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