Simon Willison’s Weblog

Agentic Pelican on a Bicycle (via) Robert Glaser took my pelican riding a bicycle benchmark and applied an agentic loop to it, seeing if vision models could draw a better pelican if they got the chance to render their SVG to an image and then try again until they were happy with the end result.

Here's what Claude Opus 4.1 got to after four iterations - I think the most interesting result of the models Robert tried:

I tried a similar experiment to this a few months ago in preparation for the GPT-5 launch and was surprised at how little improvement it produced.

Robert's "skeptical take" conclusion is similar to my own:

Most models didn’t fundamentally change their approach. They tweaked. They adjusted. They added details. But the basic composition—pelican shape, bicycle shape, spatial relationship—was determined in iteration one and largely frozen thereafter.

# 11:23 pm / svg, ai, generative-ai, llms, ai-agents, pelican-riding-a-bicycle

Scaling HNSWs (via) Salvatore Sanfilippo spent much of this year working on vector sets for Redis, which first shipped in Redis 8 in May.

A big part of that work involved implementing HNSW - Hierarchical Navigable Small World - an indexing technique first introduced in this 2016 paper by Yu. A. Malkov and D. A. Yashunin.

Salvatore's detailed notes on the Redis implementation here offer an immersive trip through a fascinating modern field of computer science. He describes several new contributions he's made to the HNSW algorithm, mainly around efficient deletion and updating of existing indexes.

Since embedding vectors are notoriously memory-hungry I particularly appreciated this note about how you can scale a large HNSW vector set across many different nodes and run parallel queries against them for both reads and writes:

[...] if you have different vectors about the same use case split in different instances / keys, you can ask VSIM for the same query vector into all the instances, and add the WITHSCORES option (that returns the cosine distance) and merge the results client-side, and you have magically scaled your hundred of millions of vectors into multiple instances, splitting your dataset N times [One interesting thing about such a use case is that you can query the N instances in parallel using multiplexing, if your client library is smart enough].

Another very notable thing about HNSWs exposed in this raw way, is that you can finally scale writes very easily. Just hash your element modulo N, and target the resulting Redis key/instance. Multiple instances can absorb the (slow, but still fast for HNSW standards) writes at the same time, parallelizing an otherwise very slow process.

It's always exciting to see new implementations of fundamental algorithms and data structures like this make it into Redis because Salvatore's C code is so clearly commented and pleasant to read - here's vector-sets/hnsw.c and vector-sets/vset.c.

# 11:38 pm / algorithms, c, computer-science, data-structures, redis, salvatore-sanfilippo, vector-search, embeddings

Fun-reliable side-channels for cross-container communication (via) Here's a very clever hack for communicating between different processes running in different containers on the same machine. It's based on clever abuse of POSIX advisory locks which allow a process to create and detect locks across byte offset ranges:

These properties combined are enough to provide a basic cross-container side-channel primitive, because a process in one container can set a read-lock at some interval on /proc/self/ns/time, and a process in another container can observe the presence of that lock by querying for a hypothetically intersecting write-lock.

I dumped the C proof-of-concept into GPT-5 for a code-level explanation, then had it help me figure out how to run it in Docker. Here's the recipe that worked for me:

cd /tmp
wget https://github.com/crashappsec/h4x0rchat/blob/9b9d0bd5b2287501335acca35d070985e4f51079/h4x0rchat.c
docker run --rm -it -v "$PWD:/src" \
  -w /src gcc:13 bash -lc 'gcc -Wall -O2 \
  -o h4x0rchat h4x0rchat.c && ./h4x0rchat'

Run that docker run line in two separate terminal windows and you can chat between the two of them like this:

# 4:04 pm / c, docker