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    Proximal aims to identify where AI models need improvement and what data could help

    A Proximal team member says the approach requires research and engineering talent on par with AI labs.

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    TLDR

    A Proximal team member describes two ways AI data companies work: fulfilling labs’ requests or proposing data needs the labs may not have identified. They say Proximal is pursuing the second approach, aiming to find where models need improvement and what data could help. They liken its work to a lab’s post-training and evaluation team and say the company is hiring.

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    2 Sources, first seen 5h ago

    Combined views

    26.6K

    2 Sources, first seen 5h ago

    269 likes
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    5h ago
    first seen 5h ago
    269 likes
    10 comments
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    11 reposts
    10 comments
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    11 reposts

    2 Sources

    @calvinchenlet me break down what’s actually happening in this market two ways companies work in this space, some a mix of both: you either have the lab tell you what to work on and what they need or you tell the labs what you think they need the former is more of a commodity but players that are large, at scale, and can react quickly usually win these deals and do well (kinda what eli mentioned here) very few are doing the latter and it’s largely greenfield - data has many open ended research problems and a competent team can definitely find something that even the labs have not worked on. this approach is much harder (requires research + engineering talent that is better than or atleast on par with the labs), but is much more interesting / valuable long term as you can tell Proximal is set up for the second approach, our goal is to be the very best in understanding where models need improvements in capabilities and what data will make them improve. this looks much more like a post training and evals team at a lab than a human data company, if this is exciting we are hiring5h
    @mobav0RT @calvinchen: let me break down what’s actually happening in this market two ways companies work in this space, some a mix of both: you…4h
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    2 Sources

    @calvinchenlet me break down what’s actually happening in this market two ways companies work in this space, some a mix of both: you either have the lab tell you what to work on and what they need or you tell the labs what you think they need the former is more of a commodity but players that are large, at scale, and can react quickly usually win these deals and do well (kinda what eli mentioned here) very few are doing the latter and it’s largely greenfield - data has many open ended research problems and a competent team can definitely find something that even the labs have not worked on. this approach is much harder (requires research + engineering talent that is better than or atleast on par with the labs), but is much more interesting / valuable long term as you can tell Proximal is set up for the second approach, our goal is to be the very best in understanding where models need improvements in capabilities and what data will make them improve. this looks much more like a post training and evals team at a lab than a human data company, if this is exciting we are hiring5h
    @mobav0RT @calvinchen: let me break down what’s actually happening in this market two ways companies work in this space, some a mix of both: you…4h