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Why AI labs are shelving their best models - Dylan Patel

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Why AI labs are shelving their best models - Dylan Patel

Transcript

31 segments

0:00

The best model that exists in the world

0:01

was trained in February. We've already

0:02

seen a [music] huge slowdown for the AI

0:05

labs, right? This regulation that they

0:07

advocate for is [music] actually slowing

0:08

down the labs a lot more than it slows

0:10

down, you know, sort of the open-source

0:11

Chinese language models. [music] You

0:12

know, OpenAI not releasing Astra, OpenAI

0:16

stopping training for 2 weeks, Anthropic

0:18

not releasing what their safety

0:19

assessment [music] said is model 2,

0:21

which is widely believed to be the next

0:23

version of Methuselah.

0:24

>> [music]

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>> They're clearly not releasing their best

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models, and in which case their revenue

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per megawatt stalls or even can start to

0:30

decline again because other models are

0:31

competitive again. So, it's not that

0:33

they're falling behind, it's just that

0:34

they're not releasing their best stuff.

0:35

[music] What if there is some regulatory

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impact that prevents them from releasing

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their best models? Now, their revenue

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per megawatt does [music] not climb as

0:42

fast, then their ability to buy that

0:43

incremental compute for a higher price

0:45

than everyone else

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>> [music]

0:46

>> starts to diminish.

Interactive Summary

The video discusses the potential negative impacts of AI regulation on leading AI labs, suggesting that such measures might be hindering their ability to release their best models and maintain a competitive edge in revenue and compute acquisition.

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