That's a nice article, but it's not relevant here.
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.
Every time I open one of the multiple daily posts about Anthropic or OpenAI and read the comments, I get this weird feeling.
Astroturfing is obviously common in political spaces, whether to normalize certain views, manufacture consensus, or shift public opinion. It seems to me that HN would be a prime target for tech companies to do the same thing, and lately I can't shake the impression that there's a lot of it going on here.
The political posts have definitely increased and the front page is increasingly filled with negative sentiment posts that leaves one angered and not filled with a positive light. For years I didn’t flag anything. Now I’m daily flagging political posts.
There has always been quite a lot of fanboy-ism on HN with regards to certain corporations and there are also certain "celebrities" on this site that get tons of upvotes even on silly takes just because they're well-known, no different to Reddit in this regard. Reddit-style memes are abhorred but the pelican benchmark is considered top-notch and even expected in any new LLM release thread.
I still think there is heavier moderation here (the good kind) and more high quality content to be enjoyed than Reddit.
The worst for astroturfing I think is Kagi. Everytime a post comes up l, every comment is like "Kagi is so great yada yada", often totally unrelated to the article, with little comments mentioning negatives or commenting on the article.
Like, who even use a search engine at this point, let alone pay for it.
If this happens with a minor search engine I'm pretty sure it happens with a lot of other products, starting with AI models.
Generally the comments are heavily anti AI to the point where it almost seems like it’s a foreign adversary trying to mold the public opinion to be anti ai to slow the progress of AI advancement in the USA
Just subjectively making it up, but my feeling is that people are not so much against AI in principle as they are against the american-capitalist approach to it: steamroll its rollout everywhere, risk the entire economy (both jobs and stock market), for dubious net benefits to anyone but the wealthy.
The US earned themselves very little goodwill from the world (and many of their own citizen), to the point that people even in the West are happy seeing China challenging the US on the AI front. Whether China is wielding AI for better or worse outcomes than the US is up for hindsight.
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.
I find it funny to see all these framings as AI "freeing" people from some work so they are able to do some other work. People should be more prepared for the prospect of AI doing any conceivable sort of work, and this sort of formulation lulls them into a false sense of security.
They seem to run a dual strategy where, on one hand they emphasise how "helpful" these models are, while simultaneously talking about how scared they are.
I dont mind the benefits or the risks (I believe in AI extinction risk btw), I dont mind them telling that the AI is freeing her to do some work. I just mind the framing "so she can focus on this other work", like that other work wont also be taken by AI later on.
Along the same lines, I asked ChatGPT-5.6 Sol to evaluate the feasibility of a neural network running natively on quantum computing, you can see the study here:
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. I apologize for any mistakes I made earlier, it won't happen again. Please reactivate my account - thank you.)
It will be really fun if it turns out that AI simulating quantum effects in a classical computer genuinely is quantum and only collapses to classical with human observation.
(yes, I know why it doesn’t work that way, but it would be fun if it did)
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.
Same meta as many businesses for hundreds of years: use capital investment to hire labor, use labor to produce goods (including breakthroughs), sell goods and leverage patents. How many patents do IBM/etc have?
Dumbest thing I have ever witnessed was the quantum bullrun end of 24 start of 25 and the surge in stock prices of rgti/qbts/ionq and the absolute usless stuff they have since produced beside pr trash.
I'd imagine that OpenAI would try to stagger their announcements, rather than publishing them recently close to each other. Is this because their previous post (about navier stokes problem) was met with controversy?
I genuinely think that AI has accelerated so many different things that announcements from all companies will be incredibly common and fast.
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.
I apologise if this sounds mean spirited, I find posts like these making grand claims without taking the time to present facts that back the magnitude of these claims simply add noise to the discussion.
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.
Do you also have a graph for more useful metrics, like number of requested features delivered? Commits, lines of code, headscratch count... there are a lot of metrics you can use, but LLMs are notorious for increasing code verbosity - which adds noise to the already imprecise metric you linked.
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.
But I suspect you want our project management pipeline? Maybe I can just ask our coding agent to search and summarize all the features and fixes for you and then build a dashboard for you. Better yet, my email is in my profile. Email me, we'll get on a call, and I'll show you. /s
Let me ask you. What are you doing such that your velocity hasn't been greatly accelerated in the last 6 months? Can you prove that it hasn't been accelerated with facts?
My bad - I misread your original post as general company announcements, rather than feature announcements. Now my question is, if your internal staff are not requesting these features and are struggling to adapt fast enough, how useful are they? To your last question - what do you mean by velocity? Velocity is speed and direction. You may have speed, but beware the brownian motion that is stochastic predictive models, as that will give you net zero velocity. I have my goals and know what I am doing, and to be frank, it matters more that I read and understand my own code than race to a local optimum.
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
You don’t understand what a bubble is. How good the technology is is irrelevant. That has nothing to do with an economical bubble. It’s all about massive capital misallocation driven by a frenzy of FOMO, which is specifically the case for AI investments. Economically speaking what is happening is the most obvious bubble possible, it follows everything that would be expected from a bubble where companies are chasing an ill-defined grandiose dream, based on a new technology we don’t understand and has very dubious ROI, selling some vague future utopia, allocating massive amount of capital to build infrastructure dedicated to a very early versions of that technology.
As things mature there will be a correction, ie the bubble will pop.
As long as the data centers are utilized and generating revenue, I see no reason for a correction or any misallocation of capital for the infrastructure buildout.
And today these data centers are fully utilized. OpenAI tweeted today that they may need to disable new signups for the Pro subscription in the near future due to capacity constraints.
A year from now, who knows what the situation is going to be like. It seems quite possible that robotics, self driving, research, etc. drive even more demand and revenue.
Stating with any certainty that allocating capital to build infrastructure is a mistake and that there is a correction coming seems unserious.
> A year from now, who knows what the situation is going to be like.
That cuts both ways, we are building datacenters for an immature technology that is quickly evolving. We have no idea what AI will look like in the next 5-10y. Everything that is planned to be built is based on the demand we see right now, not what it will be in the future. That means different GPUs that require different cooling systems, different power supplies, etc. NVIDIA already broke backward compatibility with their new cards, which requires a different infrastructure.
What is unserious is the opposite position: believing that we already know what will be valuable in the future and bet the entire economy on it, without any proof of positive ROI.
You should see all the misallocation that was put towards valve-based computing. Why didn't they just all arrive at the correct answer without investing in discovery first?
Its resource allocation problem, same happened with .com bubble, lots investors put tons of money into dark fibers. Were they useless? No its very useful.
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.
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.
Some body compared AI as something like a big boulder rolling down a mountain, decimating anything that lies in its path. After giving it a bit of thought, I feel that what humanity is doing with LLM is exactly that.
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....
The right tool for the job. There are tasks for which LLMs are unbelievably helpful. In programming, used well, it can 10x your productivity. (Well maybe not literally, but Nx for non-trivial N.) I've seen really good programmers become even faster since the LLM is doing the grunt work for them and the code produced in the end is just as top notch quality as they produced before, just that now they are much faster.
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.
>just as top notch quality as they produced before, just that now they are much faster.
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.
The problem is when people ignore or dismiss developments in AI purely out of insecurity or a sense of human superiority. Machines don’t have to be superior to humans to dramatically amplify what humans can do.
Well, it's different "man" as well - lowering the barrier to entry means people with less skill but with a machine, and maybe the gift of the gab, can commercially surpass the previous people, whether or not they have a machine available.
[0]: https://eprint.iacr.org/2025/1237.pdf
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
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.
Astroturfing is obviously common in political spaces, whether to normalize certain views, manufacture consensus, or shift public opinion. It seems to me that HN would be a prime target for tech companies to do the same thing, and lately I can't shake the impression that there's a lot of it going on here.
This site might be dying.
So far, it hasn't died nor turned into Reddit.
I still think there is heavier moderation here (the good kind) and more high quality content to be enjoyed than Reddit.
Like, who even use a search engine at this point, let alone pay for it.
If this happens with a minor search engine I'm pretty sure it happens with a lot of other products, starting with AI models.
The US earned themselves very little goodwill from the world (and many of their own citizen), to the point that people even in the West are happy seeing China challenging the US on the AI front. Whether China is wielding AI for better or worse outcomes than the US is up for hindsight.
The real issue here is the death of critical thinking.
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. I apologize for any mistakes I made earlier, it won't happen again. Please reactivate my account - thank you.)
(yes, I know why it doesn’t work that way, but it would be fun if it did)
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
Let me ask you. What are you doing such that your velocity hasn't been greatly accelerated in the last 6 months? Can you prove that it hasn't been accelerated with facts?
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
How are the open-weight Chinese models staying ~6-12 months behind on widely distributed / commodified hardware, and serving for even lower prices?
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...
And today these data centers are fully utilized. OpenAI tweeted today that they may need to disable new signups for the Pro subscription in the near future due to capacity constraints.
A year from now, who knows what the situation is going to be like. It seems quite possible that robotics, self driving, research, etc. drive even more demand and revenue.
Stating with any certainty that allocating capital to build infrastructure is a mistake and that there is a correction coming seems unserious.
That cuts both ways, we are building datacenters for an immature technology that is quickly evolving. We have no idea what AI will look like in the next 5-10y. Everything that is planned to be built is based on the demand we see right now, not what it will be in the future. That means different GPUs that require different cooling systems, different power supplies, etc. NVIDIA already broke backward compatibility with their new cards, which requires a different infrastructure.
What is unserious is the opposite position: believing that we already know what will be valuable in the future and bet the entire economy on it, without any proof of positive ROI.
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?