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This contains spoilers. This isn’t really a review, but maybe just free writing about a game I really enjoyed, recently. Maybe that is a review haha not sure. This is a story mode action adventure explorer type like Borderlands, walking dead, life is strange, and many others. Where, you Control a protagonist, in this case a cat,, 🐈, interacting with other characters in the game, as well as exploring your world to solve mostly 3 -space geometry puzzles, of , how to navigate a cat , with jumps and crawl spaces....

First, an embedding table was created, using langchain pgvector. (TODO show that example). Initial query which was working, using, a chosen_embedding, of some uuid I randomly picked from the vector table, using the cosine similarity <=> as an ORDER BY, explain analyze with myblah(chosen_embedding, chosen_id) as ( values ( (SELECT embedding FROM langchain_pg_embedding WHERE id = '280aefd0-cb15-4a54-924d-aab37ee8a816' ), '280aefd0-cb15-4a54-924d-aab37ee8a816') ) SELECT substr(id, 0, 8) as id, substr(document, 0, 40) as doc, round( 1 - cast(embedding <=> chosen_embedding as numeric), 3 ) as score, cmetadata->'name' as name FROM langchain_pg_embedding, myblah WHERE id !...

I had this interesting situqtion, where I wanted to plot some numbers that were nested inside of struct columns. They were row counts in a delta table history output, but in any case, I tried to plot them, but my plot treated them as categories. Ok realizing they were strings, I cast them to integers, but then I got nulls. After a bit of trial and error I realized they were probably laerger than 32bit!...

placeholder. didnt get chance to write this up yet, but I had used langchain pgvector, to add embeddings to postgresql , I ran my queries, and noticed they were slow. I read about pgvector indexing, and on psql, noticed my embedding column was missing an index! I tried adding the HNSW index manually. Weird error about no dimensions on the vector column. ok learned need explicit dimension. Added it. Nice adding index worked....

motivation I know more about Databricks for distributed computing. But there is also the Kubernetes world. Let’s read some more on that. Was wondering hmm, I have used Tensorflow, pytorch on standalone VMs in the past and I know that Spark has its own distributed libraries, so do Tensorflow, pytorch natively support spark, hmm? lingering questions (1) What are the dominant technologies for distributed computing? (spark, and containerization by K8S) (2) specifically GPU vs cluster based, are these alternatives?...