An experiment of adding recommendation engine to your app using pgvector search

Wow! Thank you for sharing this. I am bookmarking this article for future use! ( Truth be told, I did not fully understand everything but hopefully future me would )

Reminds of that article about Postgres for everything: https://github.com/Olshansk/postgres_for_everything

and you can also advertise your app with “uses AI” to boost investor interest by 10x instantly, 2 birds w/ one stone.

This will get you very basic recommendations, which is a nice start. But will be quite limited.

But you could, and have been able do this just as easily with compression.

Compress A. Measure the file size.

Compress B. Measure the file size

Compress C. Measure the file size

Compress A + B. Measure the file size. Compare it to (the size of A + the size of B). If A and B are similar the compressed file size will be much smaller than the combined file size of A compressed + B compressed.

Compress A + C. Measure the size. If A and C are similar the compressed file size will be much smaller than the combined file size of A compressed + C compressed.

Compress B + C. Measure the size.

Also see Simon Willison work on using embeddings for similarities: https://simonwillison.net/2023/Oct/23/embeddings/#related-co...