Why not use both? I just built a pipeline for document data extraction that uses PaddleOCR, then Gemini 3 to check + fix errors. It gets close to 99.9% on extraction from financial statements finally on par with humans.
This paper is basically statistical mechanics with a quantum veneer. Two major issues:
1. Scale: They're simulating just 13 qubits with QuTiP and making grand claims about quantum thermodynamics. The computational complexity they're glossing over here is astronomical. Anyone who's actually worked with quantum systems knows you can't just handwave away the scaling problems.
2. Measurement Problem: Their whole argument about instantaneous vs time-averaged measurements is just repackaging the quantum measurement problem without actually solving anything. They're doing the same philosophical shell game that every "breakthrough" quantum paper does by moving around where they put the observer and pretending they've discovered something profound.
This seems like a big step forward in terms of running specific use-case trained inference locally, right? At least given current hardware generally deployed in business.
This is such a bummer, but not shocked they're out-of-bounds given the bullets in the letter and how big they've become: https://www.cftc.gov/csl/22-08/download
That Twitter thread made me MORE of a believer that Dall-E has a language its own. As others said, seems like the argument is more about defining "language".