How GPT‑5.6 Sol helps run quantum computing experiments
openai.com
openai.com
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.
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.
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
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.
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.
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.
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.
People are burnt twice shy and have become comically cynical. Your discernment has been completely shot.
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.
(yes, I know why it doesn’t work that way, but it would be fun if it did)
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.)
This has always been the end game
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.
Not just techies : every serious financial analyst would check the buzz on sites like HN - but scam-altman doesn't care.
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.
Our own Github commits volume seem to follow quite closely with token usage on Open Router:
Do you also have a graph for more useful metrics
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.
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?
Now my question is, if your internal staff are not requesting these features and are struggling to adapt fast enough, how useful are they
have you considered the consequences of that or are you still drunk and thinking that this is a good thing?
And your solution to staff being unable to handle the number of feature announcements be like..?
What exactly would AI have to do in order to not be called a bubble?
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.
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.
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?
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.
Just because the bond markets 1/2/3/5-year bonds are bloated does that mean the bubble will pop. It just increases the risk.
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?
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.
Well at least as long as they don’t develop consciousness of their own.
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.
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.
> 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.
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?
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.