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Comment by eis | Hacker News Reader

Grok, Meta, Gemini and others all released updates to their models within around a month or two from their respective last release and made significant jumps in benchmarks all around the same time. Any guesses as to why that is? Is it just the release season and/or everyone is benchmaxxing?

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its essentially the same model being trained continuously 24/7 with the company periodically publishing just a new checkpoint

each new checkpoint can benefit from better reasoning training, RL on specific tasks and more synthetic data

So why do they seem to release around the same time ? my guess is because they time major releases around quarterly earnings, investor meetings and other important business milestones. Once one company announces a major update, the others also have an incentive to ship their latest checkpoint rather than look like they r falling behind.

Sure, they are just checkpoints, that much I guess is obvious. The question is why did they not do frequent releases like this before and why are they making significant jumps in benchmarks so fast and all these companies suddenly falling into that pattern? Earning reports are not to come until end of October, that's not it.

possibly the beginning of the recursive feedback as models begin to aid in their own improvement? especially algorithmic improvements, which seems to have a lot of wide open space for gains

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