Wikipedia search-by-vibes through millions of pages offline (via) Really cool demo by Lee Butterman, who built embeddings of 2 million Wikipedia pages and figured out how to serve them directly to the browser, where they are used to implement “vibes based” similarity search returning results in 250ms. Lots of interesting details about how he pulled this off, using Arrow as the file format and ONNX to run the model in the browser.
Recent articles
- Putting Gemini 2.5 Pro through its paces - 25th March 2025
- New audio models from OpenAI, but how much can we rely on them? - 20th March 2025
- Calling a wrap on my weeknotes - 20th March 2025