Hi, I wrote this a few weeks ago. Didn't expect to see this here, etc., etc.

Happy to answer any questions. We have a discord https://marin.community/

A very academic way of saying We have all the data in the world, except the data we actually need. You ask a company how something works and they say:

"Oh, theres a process."

Great. Where is it documented?

"in a spreadsheet."

Which spreadsheet?

"Well, theres the old spreadsheet, new spreadsheet, and the spreadsheet that Karen maintains."

Where's Karen?

"She left in 2021."

A posttraining data commons and the infrastructure surrounding it is the next great open source project IMO, akin to Postgres or Linux.

The Marin project from Stanford (and I believe now ran by Openathena, the authors of this blog post) is really promising and cool: https://marin.community/

What gets me excited about this project is its legibility for philanthropy, like how the Internet Archive is the destination for random recordings found in Grandma's attic.

Having a trusted steward to handle the anonymization and eval design process could kickstart a world where retiring tax accountants, or even active and generous ones, are willing to donate their data to the posttraining commons at a scale that's actually much larger than the "data industry".

I think a post-training common would have to be somewhat protected, since these things would be created with great effort and would potentially impact people's ability to earn money in their jobs.

I could also imagining them happening as state projects for the sake of competitiveness.

post training is both the future and the secret sauce.

The next iteration of AI assisted devs will not have all the devs use the same harness and model like most do now.

Instead, devs will build their own post trained models that are experts of their own domain, that have their secret sauce..

I imagine any dev would want most of those models to be something they can self host because of multiple reasons - one of them being that their employers or customers might not agree to use a cloud hosted or managed model. Plus, costs. And control.

Post training is in the future because we haven't yet reached a shared agreement on what that first "good enough" model will be like - and also because the current AI scape is in a state of flux where post training will have a lot of churn.

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