5 min read
Why robots forget, and what I'm doing about it
An honest look at the on-device data problem facing humanoid robots and self-driving stacks — and the embedded engine I built to fix it.
4 posts tagged benchmarks.
An honest look at the on-device data problem facing humanoid robots and self-driving stacks — and the embedded engine I built to fix it.
text-embedding-3-large produces 3,072-dim vectors, and most vector pipelines truncate them to stay performant. Here's what happened when we benchmarked the full dimension end-to-end.
A walk-through of the actual token math — where the savings come from, what they don't help with, and how I'd reproduce them in your codebase.
The conventional wisdom on vector search is that you have to pick two of three — recall, speed, footprint. Here's what our engine does on the dbpedia-openai benchmark.