Reposted by Eugene Yan
I’ve seen semantic IDs pop up but never bothered to actually look into them. This write up from @eugeneyan.com is a great intro that also illustrates why they’re pretty interesting for mixing recsys and LLMs eugeneyan.com/writing/sema...
eugeneyan.com
How to Train an LLM-RecSys Hybrid for Steerable Recs with Semantic IDs
An LLM that can converse in English & item IDs, and make recommendations w/o retrieval or tools.
!["...I joined a hedged fund, Renaissance Technologies, I'll make a comment about that. It's funny that I think the most important thing to do on data analysis is to do the simple things right. So, here's a kind of non-secret about what we did at renaissance: in my opinion, our most important statistical tool was simple regression with one target and one independent variable. It's the simplest statistical model you can imagine. Any reasonably smart high school student could do it. Now we have some of the smartest people around, working in our hedge fund, we have string theorists we recruited from Harvard, and they're doing simple regression. Is this stupid and pointless? Should we be hiring stupider people and paying them less? And the answer is no. And the reason is nobody tells you what the variables you should be regressing [are]. What's the target. Should you do a nonlinear transform before you regress? What's the source? Should you clean your data? Do you notice when your results are obviously rubbish? And so on. And the smarter you are the less likely you are to make a stupid mistake. And that's why I think you often need smart people who appear to be doing something technically very easy, but actually usually not so easy.]
[[at] my hedge fund, which was not a very big company, we had 7 Phd's just cleaning data and organizing the databases]"](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:ilhs5ksfpze2l5rqgig4ycl6/bafkreiblk7ckawi7cdgnaven5ulbt767s7gs56nreoa7s4cdsjj35jdoo4)