I am once again shocked at how much better image retrieval performance you can get if you embed highly opinionated summaries of an image, a summary that came out of a visual language model, than using CLIP embeddings themselves. If you tell the LLM that the summary is going to be embedded and used to do search downstream. I had one system go from 28% recall at 5 using CLIP to 75% recall at 5 using an LLM summary.
Recent articles
- Claude Sonnet 4.5 is probably the "best coding model in the world" (at least for now) - 29th September 2025
- I think "agent" may finally have a widely enough agreed upon definition to be useful jargon now - 18th September 2025
- My review of Claude's new Code Interpreter, released under a very confusing name - 9th September 2025