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
- Live blog: Claude 4 launch at Code with Claude - 22nd May 2025
- I really don't like ChatGPT's new memory dossier - 21st May 2025
- Building software on top of Large Language Models - 15th May 2025