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.
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.
> filled with negative sentiment posts that leaves one angered and not filled with a positive light
You mean the negative sentiments that you get when people uncover how big tech/monopolies/government really works ? I guess you would rather read la-la-land stories about the entrepreneurial aces of the 2010s when techies and the general populace were still gullible for that.
Negativity doesn't have to fill every space, even if you can find negativity everywhere. Maybe what HN has implicitly (and maybe explicitly) nurtured is intellectual curiosity for the sake of intellectual curiosity, which, in mi opinion es very orthogonal to negativity (even if it's intellectual adjacent).
I understand that maybe this is not what everyone wants (or understands) from HN, but I do sympathize with the other comment: after visiting HN I'd rather be happy and curious that angered and curious
Yes. That’s not what I want to read on hn. You can go to Reddit or many other places for that and fill yourself with anger all you want. I personally do not want that for me and if hn continues the way it’s headed then I’ll block it like I did Reddit.
There’s a difference between on-topic discussions relevant to the post and “discussions” that veer off into the same emotional tribal rants that we see constantly now. We try to ignore it but the constant negativity and “us vs them” is not healthy, let alone meaningful discussion.
As I'm always telling people, the phenomenon you're noticing is that the President of the United States wishes to increase negative sentiment and widen the scope of things which are subject to politics. It's not something that HN or its users get a choice in. If you don't like it, I'm with you, but you're going to have to take it up with him.
Depends how you define it. I mean, just because you or the moderators say so doesn't make it true - I've used this site for more than 10 years and I've never seen a higher proportion of political posts nor a higher proportion of blatantly partisan comments on most (not just political) threads.
It isn't like this site would be likely to die in the sense of 0 people visit it, so I'm not sure what you even mean by it dying and have no clue how you'd even measure that. For all you know, most of the commenters are bots - I could be a bot for all you know. But the quality of discourse has definitely become less tech-focused since I first started coming here, and as a Reddit user from early on it very much reminds me of that. Reddit in the beginning was basically to Digg what HN is to Reddit today, and the trajectory is - subjectively to me at least - very similar. What started out as a nerdy tech space slowly over time has and is morphing into political bullshit that never would have made the front page 10 years ago.
Having said that, there's no doubt all these sites have astroturfing issues, and tech in particular tends to have very vociferous users as a rule.
> What started out as a nerdy tech space slowly over time has and is morphing into political bullshit that never would have made the front page 10 years ago.
Don't you see how we're propagating the problem here? It would be easy for someone who wants a nerdy tech space to read and discuss the contents of the source article, describing how a new technology might change the experimental process for quantum computing research. Instead we're engaging in political meta-commentary, under an OP comment speculating that "[t]his site might be dying" because they don't like hearing about the company who published it.
When it gets to politics or economics there are an increasingly large amount of reddit like socialism comments. It seems ironic given its run by a VC firm.
Yeah I’m gonna have to go ahead and push back on this. It’s getting worse and trending towards Reddit and using that guideline to tell people to stop talking about it is making things worse. We need to shame and downvote and flag the Reddit-tier posts and comments here.
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
I think this is some sort of built-in bias we all have. I'm pretty bearish on AI, and to me I get the impression that generally most comments are heavily pro-AI, or pro-OpenAI/Anthropic. I think we're just biased to see and remember what we disagree with.
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.
Possibly the only more totalizing steamrolling approach to development than the American-capitalist is the socialist-big-push. This complaint is nonsense.
I'm not anti-AI; I'm anti-centralization of power. If the Chinese models were closed source and developed with the same strategy as the US labs then I'd be rooting against them, too.
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.
The whole thread without a single technical post about the significance (or not) of the announcement. Who want to follow me to create a new site that focus on the substance of the news?
I'm not abandoning HN, I can come back here to make fun of posts I don't like, post shallow comments, snarky ones, vent my conspiracy theories, complain about the evils that are S, A or E, post my personal anecdotes, advocate for my beliefs which I'm convinced as the only truth. Last but not least, feel smug posting about AI sounding posts. HN is a great place for all of that.
LLMs are advancing the frontiers of knowledge. Is it really that hard for you to believe that people are simply genuinely fascinated about these developments?
People are burnt twice shy and have become comically cynical. Your discernment has been completely shot.
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.
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)
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.)
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?
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.
I feel like, given how poorly techies view OAI and its executive team, they'd be better off not releasing PR (ie., IPO-farming) announcements like this.
If you've got something objectively monumental to announce then sure I guess (I mean, most of us will just assume OAI is lying/exaggerating), but nobody takes the OAI propaganda seriously. You might even say this is not how you make your first billion.
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.
"Compute" is not one generic commodity. Filling your datacentres with ASICs that do nothing but compute SHA256 for Bitcoin mining was a smart move in 2015 but today that hardware is worthless e-waste.
What does the depreciation curve look like for nvidia cards purchased today? How long will it take to recoup the investment on this buildout? Will those datacenters pay for themselves before they're scrapped?
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....
I saw the GP as a snarky riposte against the doomerism of the anti-AI crowd.
Technology has been augmenting or replacing human work for as long as the first slab of rock was shoved up an inclined plane (wedge) and popped into its spot in the Great Pyramid.
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.
> > just as top notch quality as they produced before, just that now they are much faster.
> No, they are not.
It fascinates me with what conviction you are writing this. You don't know any of the people involved nor how they work or the code they produce. Yet you are certain that what I wrote is false.
I'm speculating now, but you are likely imagining that the LLM-produced code is used as-is, producing a growing slop pile. The cases I'm describing are not like that. Those folks know exactly what they want, how the architecture and the code should look like, and they are getting the LLM to produce it like that. There are quite a few iterations and manual polishing steps too. In the end, the code looks like as if they had written it themselves, just that the whole process was 5x as fast because there is so much quite standard stuff automatically added which would just have been slower by hand.
If you have not experienced this yourself then I understand your attitude, but rest assured, this is possible and I'd caution you to dismiss this.
Of course I disagree because this generalized statement is quite obviously false. Have you used electronics made by hand? Versus made by a machine? You can't possibly claim that a PCB assembly by hand has higher quality than done by a machine. That the transmission of a message by hand from Berlin to Paris is higher quality than if communictations electronics was involved.
Of course you didn't mean that (but you wrote it). You probably mean a creative process. The process I descibed is still having the creative human in the loop. Just that the machine is filling in the gaps that are qualite mechanically fillable. Nothing strange with that.
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.
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.
Even with AI you'd want the AI to be writing python scripts instead of following an analysis.md.
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
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.
This is a fantastic way to use a C64!
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
My C64 is going to absolutely smash this and my dog (Darby) is a frequent barker too! I'll vibe up an abacus emulator as a PWA.
Made my day, thanks :)
Is it a version that has not yet been nerfed? Since yesterday I noticed Sol and Astra have become much dumber.
Something about the look of quantum computers takes me right back to the ENIAC.
OpenAI is on a quite offensive lately with pathbreaking discoveries.
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.
This site might be dying.
The death of HN has been lamented since at least 2007 (in addition to the cliche that it's turning into Reddit, mentioned in the guidelines).
So far, it hasn't died nor turned into Reddit.
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.
> filled with negative sentiment posts that leaves one angered and not filled with a positive light
You mean the negative sentiments that you get when people uncover how big tech/monopolies/government really works ? I guess you would rather read la-la-land stories about the entrepreneurial aces of the 2010s when techies and the general populace were still gullible for that.
Negativity doesn't have to fill every space, even if you can find negativity everywhere. Maybe what HN has implicitly (and maybe explicitly) nurtured is intellectual curiosity for the sake of intellectual curiosity, which, in mi opinion es very orthogonal to negativity (even if it's intellectual adjacent).
I understand that maybe this is not what everyone wants (or understands) from HN, but I do sympathize with the other comment: after visiting HN I'd rather be happy and curious that angered and curious
Yes. That’s not what I want to read on hn. You can go to Reddit or many other places for that and fill yourself with anger all you want. I personally do not want that for me and if hn continues the way it’s headed then I’ll block it like I did Reddit.
Discussions are just discussions. You can always opt out not participate. HN's guidelines make discussions here are a lot more civil than reddit.
There’s a difference between on-topic discussions relevant to the post and “discussions” that veer off into the same emotional tribal rants that we see constantly now. We try to ignore it but the constant negativity and “us vs them” is not healthy, let alone meaningful discussion.
LinkedIn still caters to people who want more pro-corporate propaganda. Can check it out.
As I'm always telling people, the phenomenon you're noticing is that the President of the United States wishes to increase negative sentiment and widen the scope of things which are subject to politics. It's not something that HN or its users get a choice in. If you don't like it, I'm with you, but you're going to have to take it up with him.
What you’re noticing is called fifth generation warfare. Get people to feel bad about their country, government, community, etc.
> So far, it hasn't died nor turned into Reddit.
Depends how you define it. I mean, just because you or the moderators say so doesn't make it true - I've used this site for more than 10 years and I've never seen a higher proportion of political posts nor a higher proportion of blatantly partisan comments on most (not just political) threads.
It isn't like this site would be likely to die in the sense of 0 people visit it, so I'm not sure what you even mean by it dying and have no clue how you'd even measure that. For all you know, most of the commenters are bots - I could be a bot for all you know. But the quality of discourse has definitely become less tech-focused since I first started coming here, and as a Reddit user from early on it very much reminds me of that. Reddit in the beginning was basically to Digg what HN is to Reddit today, and the trajectory is - subjectively to me at least - very similar. What started out as a nerdy tech space slowly over time has and is morphing into political bullshit that never would have made the front page 10 years ago.
Having said that, there's no doubt all these sites have astroturfing issues, and tech in particular tends to have very vociferous users as a rule.
> What started out as a nerdy tech space slowly over time has and is morphing into political bullshit that never would have made the front page 10 years ago.
Don't you see how we're propagating the problem here? It would be easy for someone who wants a nerdy tech space to read and discuss the contents of the source article, describing how a new technology might change the experimental process for quantum computing research. Instead we're engaging in political meta-commentary, under an OP comment speculating that "[t]his site might be dying" because they don't like hearing about the company who published it.
When it gets to politics or economics there are an increasingly large amount of reddit like socialism comments. It seems ironic given its run by a VC firm.
[dead]
Yeah I’m gonna have to go ahead and push back on this. It’s getting worse and trending towards Reddit and using that guideline to tell people to stop talking about it is making things worse. We need to shame and downvote and flag the Reddit-tier posts and comments here.
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
I think this is some sort of built-in bias we all have. I'm pretty bearish on AI, and to me I get the impression that generally most comments are heavily pro-AI, or pro-OpenAI/Anthropic. I think we're just biased to see and remember what we disagree with.
Especially since these anti-AI comments completely disappear in posts about Chinese AI progress.
This is total bollocks. The skeptics are all present and just as forceful in any AI thread.
Give a single post as an example where the anti AI comments are prevalent?
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.
Possibly the only more totalizing steamrolling approach to development than the American-capitalist is the socialist-big-push. This complaint is nonsense.
I'm not anti-AI; I'm anti-centralization of power. If the Chinese models were closed source and developed with the same strategy as the US labs then I'd be rooting against them, too.
I thought the opposite. I've sensed the gravitational pull from 2 trillion-dollar companies that are hoping to IPO in the near future
That is the most bizarre leap given that the best models bang-for-buck right now are Chinese.
The real issue here is the death of critical thinking.
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.
Funny you should mention them but not the multiple daily posts about the Chinese models and labs.
The whole thread without a single technical post about the significance (or not) of the announcement. Who want to follow me to create a new site that focus on the substance of the news?
I'm not abandoning HN, I can come back here to make fun of posts I don't like, post shallow comments, snarky ones, vent my conspiracy theories, complain about the evils that are S, A or E, post my personal anecdotes, advocate for my beliefs which I'm convinced as the only truth. Last but not least, feel smug posting about AI sounding posts. HN is a great place for all of that.
LLMs are advancing the frontiers of knowledge. Is it really that hard for you to believe that people are simply genuinely fascinated about these developments?
People are burnt twice shy and have become comically cynical. Your discernment has been completely shot.
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.
Guess I need to update https://quantumvibecoding.org
I am wondering about using ML/AI for quantum chemistry; ORCA is S-tier software and docs, but is very slow!
It will be fun if the AI realize that quantum is not needed and just simulate the results in a classical computer
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)
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:
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.)
Results of prompts are like farts. We each have our own and aren't interested in the ones from other people.
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.
If you had a Genie, would you only use it to make more slightly less capable genies?
This has always been the end game
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?
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.
Not to downplay the risk, but I reckon it’s human nature to embrace the benefits and ignore the risks.
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.
I feel like, given how poorly techies view OAI and its executive team, they'd be better off not releasing PR (ie., IPO-farming) announcements like this.
If you've got something objectively monumental to announce then sure I guess (I mean, most of us will just assume OAI is lying/exaggerating), but nobody takes the OAI propaganda seriously. You might even say this is not how you make your first billion.
> poorly techies view OAI
Not just techies : every serious financial analyst would check the buzz on sites like HN - but scam-altman doesn't care.
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.
Another glorious random number generator experiment?
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.
I've been tracking Github commits per week for my team. Here's how it's looking:
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
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.
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.
> I feel like we've made more feature announcements to our internal staff than they can handle.
And your solution to staff being unable to handle the number of feature announcements be like..?
> more feature announcements to our internal staff than they can handle
have you considered the consequences of that or are you still drunk and thinking that this is a good thing?
They solved the code, now they're gonna solve the people away.
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This is needlessly combative and insulting.
Which company?
This is just a blogpost, rather than a major announcement (FLT proof was closer to the latter than the former)
At the rate this field is accelerating maybe this IS staggering
They are desperately rushing to IPO before the bubble bursts.
AI just solved a millennium prize problem. In a matter of days. Because of a rumor that someone else solved the same problem with AI.
What exactly would AI have to do in order to not be called a bubble?
How these things are even connected?
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
> The current prices the largest players set for their models are not profitable, they bleed money.
How are the open-weight Chinese models staying ~6-12 months behind on widely distributed / commodified hardware, and serving for even lower prices?
By distilling the US SOTA models, which is cheaper than creating from scratch.
If non AI companies, in particular non tech companies start making unprecedented amounts of profit, inflation adjusted I will concede.
That being said I think LLMs are impressive, still.
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.
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...
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.
Directionally we are seeing demand for more compute.
It's a reasonable assumption that data centers that are set up for large power usage and cooling will be valuable.
Claiming the opposite based on, well, nothing at all, in order to forecast a correction, seems less reasonable.
"Compute" is not one generic commodity. Filling your datacentres with ASICs that do nothing but compute SHA256 for Bitcoin mining was a smart move in 2015 but today that hardware is worthless e-waste.
What does the depreciation curve look like for nvidia cards purchased today? How long will it take to recoup the investment on this buildout? Will those datacenters pay for themselves before they're scrapped?
It's an interesting question. Some napkin math:
Let's say we serve a Fable class model on 8x B300.
From Kimi K3 metrics, with 8x concurrent streams, we would achieve 55-60 tok/s per stream, matching Fable 5.1 throughput.
432 tok/s x 3600 => 1.555M output tokens/h x 50$/M API price = $77.76 revenue per hour.
Assuming total API billing at 2.06x output token bill = $160.2 / hour or ~$20 per B300.
A server with 8x B300 could be $461.5k.
At an obviously unrealistic 100% utilization we would look at 4 months of revenue to match the cost of the server.
About how model serving works at scale and actual utilization I know little.
And for all we know Anthropic could serve their model with 64 streams on the same hardware instead of the 8 we assumed here.
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?
Per Anthropic's prospectus: generate $30T (~94% of 2026 US nominal GDP) in revenue.
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.
You really believe there will be less demand for AI in the future?
No, I think AI models will be cheap commodities available from hundreds of providers for a few dollars, like a Linux VM is today.
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.
I wondered what the birds were singing about every morning.
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Another one of openAI's stolen 'discoveries' for the IPO warm-up ?
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....
Let's go back to caves, this whole "civilisation" thing is not working out.
Is reductio ad absurdum the only argument pro AI crowd can come up with?
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?
I saw the GP as a snarky riposte against the doomerism of the anti-AI crowd.
Technology has been augmenting or replacing human work for as long as the first slab of rock was shoved up an inclined plane (wedge) and popped into its spot in the Great Pyramid.
The trees, man, the trees. We never should have left the trees.
It seems that humanity would have went on a lot longer if we never left the caves, so you might have a point there.
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.
> > just as top notch quality as they produced before, just that now they are much faster.
> No, they are not.
It fascinates me with what conviction you are writing this. You don't know any of the people involved nor how they work or the code they produce. Yet you are certain that what I wrote is false.
I'm speculating now, but you are likely imagining that the LLM-produced code is used as-is, producing a growing slop pile. The cases I'm describing are not like that. Those folks know exactly what they want, how the architecture and the code should look like, and they are getting the LLM to produce it like that. There are quite a few iterations and manual polishing steps too. In the end, the code looks like as if they had written it themselves, just that the whole process was 5x as fast because there is so much quite standard stuff automatically added which would just have been slower by hand.
If you have not experienced this yourself then I understand your attitude, but rest assured, this is possible and I'd caution you to dismiss this.
Many will disagree and say that anything done by humans is by far superior to anything done by machines. You don't want to correct them, do you?
Of course I disagree because this generalized statement is quite obviously false. Have you used electronics made by hand? Versus made by a machine? You can't possibly claim that a PCB assembly by hand has higher quality than done by a machine. That the transmission of a message by hand from Berlin to Paris is higher quality than if communictations electronics was involved.
Of course you didn't mean that (but you wrote it). You probably mean a creative process. The process I descibed is still having the creative human in the loop. Just that the machine is filling in the gaps that are qualite mechanically fillable. Nothing strange with that.
Machines are extensions of man, it’s not man vs machine but man with machines vs man without.
Well at least as long as they don’t develop consciousness of their own.
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.
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Yes I agree. AI has fundamental problems but a lot of "AI sucks" is the huge, trivial capability for misuse.
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