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    Teortaxes Weighs OpenAI Reasoning RL Against Anthropic Lead

    DeepSeek booster @teortaxesTex compares OpenAI and Anthropic approaches to AI progress.

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    1 Source, 29d ago, first seen 29d ago

    TLDR

    @teortaxesTex, the pseudonymous X account known as DeepSeek's most vocal online supporter, posted a clarification on model development paths. The account states the comment is not a prediction that OpenAI will win overall. It notes Anthropic gained a temporary edge through faster pretraining and agentic coding work. The post adds that OpenAI appears to hold a stronger method for reasoning RL. It also points to Chinese results as evidence that scale may be overrated for capabilities tied to recursive self-improvement.

    Combined views

    23.5K

    1 Source, first seen 29d ago

    Combined views

    23.5K

    1 Source, first seen 29d ago

    266 likes
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    266 likes
    10 comments
    61 saves
    11 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

    10 comments
    61 saves
    11 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

    1 Source

    @teortaxesTexTo be clear this is not a prediction that OpenAI will "win". Anthropic has scored a temporary lead by rushing ahead on pretraining and agentic coding. But it seems to me that OAI have a better doctrine on reasoning RL; while Chinese results suggest that scale is overrated for RSI-relevant reasoning capabilities. In combination with OAI's growing quantitative and qualitative compute advantage, they can achieve greater internal R&D velocity, and then they have Astra and whatever is next to catch up on model scale. Even if their science of pretraining is behind Anthropic (which I'm sure it is) and their "10T" is what Anthropic gets with "5T", they only need to maintain positive returns to scale, eat the costs, capitalize on greater knowledge coverage on top of better and more efficient reasoning RL, and then they're back in the lead. The medium-term OpenAI objective, then, is to keep compounding their RL advantage while their next generation pretraining project takes shape. Alignment issues (which are inseparable from horrible infra ineptitude) may slow them down, but Anthropic is clearly not perfect here either. Bullish on OpenAI.

    1 Source

    @teortaxesTexTo be clear this is not a prediction that OpenAI will "win". Anthropic has scored a temporary lead by rushing ahead on pretraining and agentic coding. But it seems to me that OAI have a better doctrine on reasoning RL; while Chinese results suggest that scale is overrated for RSI-relevant reasoning capabilities. In combination with OAI's growing quantitative and qualitative compute advantage, they can achieve greater internal R&D velocity, and then they have Astra and whatever is next to catch up on model scale. Even if their science of pretraining is behind Anthropic (which I'm sure it is) and their "10T" is what Anthropic gets with "5T", they only need to maintain positive returns to scale, eat the costs, capitalize on greater knowledge coverage on top of better and more efficient reasoning RL, and then they're back in the lead. The medium-term OpenAI objective, then, is to keep compounding their RL advantage while their next generation pretraining project takes shape. Alignment issues (which are inseparable from horrible infra ineptitude) may slow them down, but Anthropic is clearly not perfect here either. Bullish on OpenAI.