My neighbour - a few hundred metres further up the road - has two dogs, one of which a surefire genius as it has no problems barking out 334543333-bit RSA factorisations. It must have been solving NP-complete problems for years by now, night after night.

Relevant paper [0] "Replication of Quantum Factorisation Records with an 8-bit Home Computer, an Abacus, and a Dog"

[0]: https://eprint.iacr.org/2025/1237.pdf

I had qubit bring up and calibration fully automated with Python in 2011 including full spectrum measurements, lifetime characterization, Rabi/Ramsey measurements, calibration of single qubit gates and two qubit swap gates and full quantum process tomography, so not sure if AI is really needed there, curve fitting and some data logging is enough for this. Even had a nice LabView like GUI but with PyQT, it was quite nice. Still of course cool, I guess today I would just let Codex loose on some experiment goals but in the end my ability to produce results was mostly limited by the chip itself and the qubit lifetimes and theres no magic trick AI can apply to make these go up by a factor of 10. Still would’ve saved me a lot of time for routine programming tasks I imagine and that seems to be the main takeaway of the article. I guess name dropping quantum computing makes this sound cooler but in principle it’s just automation that you can apply anywhere, nothing quantum computing specific here.

So new business model meta is: acquire enough compute that you can burn millions of dollars on patentable scientific breakthroughs with unused capacity and on models nobody else has yet. That might actually kind of make sense.

Something about the look of quantum computers takes me right back to the ENIAC.

Another glorious random number generator experiment?

Another one of openAI's stolen 'discoveries' for the IPO warm-up ?

It will be fun if the AI realize that quantum is not needed and just simulate the results in a classical computer

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