Ingesting PDFs and why Gemini 2.0 changes everything

Clickbait. It doesn't change "everything". It makes ingestion for RAG much less expensive (and therefore feasible in a lot more scenarios), at the expense of ~7% reduction in accuracy. Accuracy is already rather poor even before this, however, with the top alternative clocking in at 0.9. Gemini 2.0 is 0.84, although the author seems to suggest that the failure modes are mostly around formatting rather than e.g. mis-recognition or hallucinations.

TL;DR: is this exciting? If you do RAG, yes. Does it "change everything" nope. There's still a very long way to go. Protip for model designers: accuracy is always in greater demand than performance. A slow model that solves the problem is invariably better than a fast one that fucks everything up.

If Gemini can do semantic chunking at the same time as extraction, all for so cheap and with nearly perfect accuracy, and without brittle prompting incantation magic, this is huge.

But the bounding box problem hits close to home. We've found Unstructured's API gives pretty accurate box coordinates, and with some tweaks you can make them even better. The tricky part is implementing those tweaks without burning a hole in your wallet.

This is giving me hope that it's possible.