tohms

I went back over backprop recently and it was humbling how much this stuff had faded, especially nowadays with large models that encourage passive learning in my opinion. So writing it up in public was my way of relearning it.

I tried to make it intuitive, interactive and with some details and proofs for the curious, and a few exercises at the end to practise actively.

Feedback welcome, especially if a step is unclear or something is wrong.

Thank you, the interactive parts were the actual reason I started the article, glad it helped.

Thanks ! the article is trying to explain several other papers like the Product Quantization paper which was peer‑reviewed in IEEE but i totally agree.

yeah, my read is most production users stay on CPU and if they need heavier/faster workdloads in they might often move toward managed vector services like pinecone, mongodb atlas, or pgvector, and attention follows usage. Also FAISS came out of FAIR's team in Paris, Meta’s recent massive reorganization and layoffs which splitted FAIR's team likely have an impact in its maintenance.