someone has opportunity to prepackage and even sell such product (postgres has BSD license, so you can totally close sources and sell as your own product).

Also, I think there are many cases when smaller models can totally run on CPU.

Right, but they can (and do) also prepackage ML inference services that don't involve Postgres. I think the small model use case would be the biggest reason, same as how I've sometimes used a Postgres table as a cache in a pinch.

> Right, but they can (and do) also prepackage ML inference services that don't involve Postgres.

but then you would need some dataprocessing/warehousing infra integrated to produce dataset for inference and then do something with inference results. Having one db with everything packaged would reduce complexity significantly.

I was just looking at inference, meaning you need some separate infra to do the training either way. If the DB does the training too, then yeah. I think we're pretty far from that, and Postgres by itself might not be the platform for it. There are platforms with SQL-like interfaces that use databases underneath, but there's a lot happening on top.

I think it is all few months work project, given you can run any arbitrary py/c code in extension in postgres, so it is a matter of data wrangling: convert pg table to recordio, run train/inference, convert results back to pg table, wrap logic into pg/py or pg/c functions.

Postgresml.org extension can do training. End to end ml workflows within postgres... Posting this as a happy user.