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[0]: https://eprint.iacr.org/2025/1237.pdf
The article you linked is about using quantum computer for fake big number factorization. You pick a very big number with a well known easy factorization and then use a quantum computer to factorize it, that is easy because you choose the number very carefully.
This article is about using a LLM to calibrate a quantum chip. It replace the work of a junior researcher (or something like that). In another comment, someone claims that is using a python script for this same task.
I like to think that the python script is an "expert system" that is 1980 AI, and the main article is an "large language model" that is 2020 AI. My guess is that for now the python script is better, but the LLM are advancing very fast and will catch up soon.
If you want to see other similar quantum computing exploits on 8bit computers:
https://medium.com/@dakk/quantum-computing-on-a-commodore-64... https://youtu.be/7dgAaZa22nU https://youtu.be/Mo177GGJb3g https://youtu.be/zCC3AmM1_lo
http://taonexus.com/publicfiles/sep2026/quantum_neural_netwo...
In short it's not really feasible and it suggested classical coherent photonics and in-memory compute as more viable approaches.
(Off-topic aside: these days I am more interested in funding Social Security Trust Funds (OASI & DI Solvency) - if anyone at OpenAI can help reactivate my account: rviragh@gmail.com it would let me do further studies that directly support this important goal, currently my chatgpt account was deactivated.)
This has always been the end game
In my own company, the last 2 months, I feel like we've made more feature announcements to our internal staff than they can handle. AI has genuinely made us that much faster.
In the past, making one of these announcements every month and the company celebrated. Now we're making making multiple each week.
Not only that, we're making so many tiny improvements and bug fixes that improve the experience but we don't even bother to make those announcements anymore. They don't feel "grand" enough anymore. The goal post has shifted a lot in the last 6 months.
You could've stopped with just the first sentence and I've would learned just as much as I did reading that comment to the end.
https://imgur.com/a/GvByYrD
Our own Github commits volume seem to follow quite closely with token usage on Open Router:
https://openrouter.ai/rankings
And your solution to staff being unable to handle the number of feature announcements be like..?
have you considered the consequences of that or are you still drunk and thinking that this is a good thing?
What exactly would AI have to do in order to not be called a bubble?
The current prices the largest players set for their models are not profitable, they bleed money. Eventually they will "fix" it. It could end up making their services less affordable and it could cascade other businesses and services that are dependent on them go out of business
As things mature there will be a correction, ie the bubble will pop.
I would recommend to read « Boom and Bust: a global history of financial bubbles » https://pure.qub.ac.uk/en/publications/boom-and-bust-a-globa...
If you want check a example company from the .com days check cisco, their stock peaked at 75 then crashed hard and only managed hit that again thanks for the AI bubble.
That being said I think LLMs are impressive, still.
The problem is not that it is super smart. It is that it is super dumb and super powerful. Like a boulder falling down.
Humanity is like this bunch of utter morons who has rolled a big boulder up a big mountain and let it loose at the top, and standing at the bottom is clapping and cheering seeing it coming down, guided by random collisions in its path, and with real probability that it will land on them....
Of course you can misuse it. Produce mountains of unmaintainable slop, full of issues. But that's true for every tool. Before LLMs already, and there will be future tools too.
So, careful with generalizations please. It's not all just dumb.
No, they are not. There write programs like they write prose. There is 100% adherence to grammar and spelling when they write prose, but yet what they write is unintelligible and needlessly verbose.
When they write computer programs there is 100% adherence to good practices, but eventually the program becomes so unintelligible and verbose that only an LLM can make any sense of it going forward. But even then, changes result in more things breaking than they fix. But the number of bugs slashed goes through the roof. Management is happy!
>Of course you can misuse it.
I think the proper way to use it is to use it as a better search tool. But I don't think AI marketing and valuation is going to be sated by such a use case.
Well at least as long as they don’t develop consciousness of their own.
Like, why not stick to those products of civilization that don't actively try to replace humans who just so happen to comprise this very civilization?