Reminds me of reading Programming Collective Intelligence by Toby Segaran, which inspired me with a range of things, like building search, recommenders, classifiers etc.
That was a great book, I wonder what the 2025 equivalent of it is...
Readit Newscipherself commented on Building a Simple Search Engine That Works karboosx.net/post/4eZxhBo... · Posted by u/freediver
cipherself commented on Show HN: Spam classifier in Go using Naive Bayes github.com/igomez10/nspam... · Posted by u/igomeza
12 (13?) years ago I had also written a Naïve Bayes classifier in Perl https://github.com/cipherself/NaiveBayes_perl
IIRC, next thing on my TODO list was to add vectorization. Also (like OP) it uses log probabilities to avoid floating-point underflow.
cipherself commented on Heartbeats in Distributed Systems arpitbhayani.me/blogs/hea... · Posted by u/sebg
Does anyone have recommendations on books/papers/articles which cover gossip protocols?
I have been more interested in learning about gossip protocols and how they are used, different tradeoffs, etc.
10 years ago I've implemented SCAMP (a gossip protocol) in Clojure, you might find it interesting, the implementation is quite small https://github.com/cipherself/gossip
cipherself commented on How often does Python allocate? zackoverflow.dev/writing/... · Posted by u/ingve
I admit it may just be because I'm a PL nerd, but I thought it was general knowledge that pretty much EVERYTHING in Python is an object, and an object in Python is always heap allocated AFAIK. This goes deeper than just integers. Things most think of as declarative (like classes, modules, etc.) are also objects, etc. etc. It is both the best thing (for dynamism and fun/tinkering) and worst thing (performance optimization) about Python.
If you've never done it, I recommend using the `dir` function in a REPL, finding interesting things inside your objects, do `dir` on those, and keep the recursion going. It is a very eye opening experience as to just how deep the objects in Python go.
> I recommend using the `dir` function in a REPL
A while back I wrote this https://mohamed.computer/posts/python-internals-cpython-byte..., perhaps it's interesting for people who use `dir` and wonder what some of the weird things that show up are.
cipherself commented on Production RAG: what I learned from processing 5M+ documents blog.abdellatif.io/produc... · Posted by u/tifa2up
I think he just means it should be assumed to be standard practice and considered baseline at this point.
Assuming that's what he meant, why would it be considered baseline versus anything else? I am genuinely curious because I'd like to know more about issues people face with this or that vector store in general.
cipherself commented on Code from MIT's 1986 SICP video lectures github.com/felipap/sicp-c... · Posted by u/felipap
If you are into SICP, you would probably like a nicely formatted html version of the book:
https://sarabander.github.io/sicp/html/index.xhtml#SEC_Conte...
And also this:
Moreover, you can have SICP inside emacs by just downloading a package from Melpa:
cipherself commented on Production RAG: what I learned from processing 5M+ documents blog.abdellatif.io/produc... · Posted by u/tifa2up
Yes, AI Search has a new agentic retrieval feature that includes synthetic query generation: https://techcommunity.microsoft.com/blog/azure-ai-foundry-bl...
You can customize the model used and the max # of queries to generate, so latency depends on those factors, plus the length of the conversation history passed in. The model is usually gpt-4o or gpt-4.1 or the -mini of those, so it's the standard latency for those.
A more recent version of that feature also uses the LLM to dynamically decide which of several indices to query, and executes the searches in parallel.
That query generation approach does not extract structured data. I do maintain another RAG template for PostgreSQL that uses function calling to turn the query into a structured query, such that I can construct SQL filters dynamically. Docs here: https://github.com/Azure-Samples/rag-postgres-openai-python/...
I'll ask the search about SPLADE, not sure.
Got it, I think this might make sense for a "conversation" type of search not for an instant search feature because lowest latency is gonna be too high IMO.
cipherself commented on Production RAG: what I learned from processing 5M+ documents blog.abdellatif.io/produc... · Posted by u/tifa2up
Not here to schlep for AWS but S3 Vectors is hands down the SOTA here. That combined with a Bedrock Knowledge Base to handle Discovery/Rebalance tasks makes for the simplest implementation on the Market.
Once Bedrock KB backed by S3 Vectors is released from Beta it'll eat everybody's lunch.
S3 Vectors is hands down the SOTA here
SOTA for what? Isn't it just a vector store?
cipherself commented on Production RAG: what I learned from processing 5M+ documents blog.abdellatif.io/produc... · Posted by u/tifa2up
At Microsoft, that's all baked into Azure AI Search - hybrid search does BM25, vector search, and re-ranking, just with setting booleans to true.
It also has a new Agentic retrieval feature that does the query rewriting and parallel search execution.
Disclosure: I work at MS and help maintain our most popular open-source RAG template, so I follow the best practices closely: https://github.com/Azure-Samples/azure-search-openai-demo/
So few developers realize that you need more than just vector search, so I still spend many of my talks emphasizing the FULL retrieval stack for RAG. It's also possible to do it on top of other DBs like Postgres, but takes more effort.
I am working on search but rather for text-to-image retrieval, nevertheless, I am curious if by that's all baked into Azure AI search you also meant synthetic query generation from the grandparent comment. If so, what's your latency for this? And do you extract structured data from the query? If so, do you use LLMs for that?
Moreover I am curious why you guys use bm25 over SPLADE?
[0] https://www.freedesktop.org/software/systemd/man/latest/syst...
[1] https://www.freedesktop.org/software/systemd/man/latest/syst...
[2] https://www.freedesktop.org/software/systemd/man/latest/syst...
[3] https://www.freedesktop.org/software/systemd/man/latest/syst...