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Frаnçois
282 posts
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Frаnçois

@fpaupier
Engineer - software, data, AI/ML
Earth
fpaupier.fr
Joined May 2018
595
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117
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  • user avatar
    Frаnçois
    @fpaupier
    Jan 14
    "reinforcing the absolute criticality for insanely high talent density"
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    GIF
    user avatar
    Stanislas Polu
    Dust
    @spolu
    Jan 13
    Build vs Run and zero-sumness: a simple framework to reason about how to scale teams post artificial intelligence abundance. Will AI annihilate all head-counts? I posit it's not quite the case especially for run functions that are inherently a zero-sum game in the market.
  • user avatar
    Frаnçois
    @fpaupier
    Oct 21, 2025
    big indeed. A new dimension for training data collection with clearer reward definition. Exciting times for the oai RL folks
    user avatar
    swyx
    AI Engineer
    @swyx
    Oct 21, 2025
    tweeting this from chatgpt atlas! very excited about this. this is the single biggest step up for OpenAI in collecting your full context and giving fully personalizable AGI. Context is the limiting factor and as @pmarca said, the browser is the new operating system. the only
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  • user avatar
    Frаnçois
    @fpaupier
    Oct 2, 2025
    interesting to see jetbrains trajectory with their products being severely challenged by a IDE-less future with terminal based dev - they're reaching out to their user for feedback on in-IDE LLM tools usage and pretty happy with their progress last semester tbh
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  • user avatar
    Frаnçois
    @fpaupier
    Sep 30, 2025
    interesting to see Z dot ai propose quarterly plan for their claude (clawd?) code API like code agent. No one serious is committing to a yearly plan on a model provider given monthly SOTA rotations among labs
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  • user avatar
    Frаnçois
    @fpaupier
    Sep 4, 2025
    love this rich format blog post with actual data points in the article
    user avatar
    Luis
    @lusxvr
    Sep 4, 2025
    Today, we are releasing FineVision, a huge open-source dataset for training state-of-the-art Vision-Language Models: > 17.3M images > 24.3M samples > 88.9M turns > 9.5B answer tokens Here are my favourite findings:
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