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How GPT‑5.6 Sol helps run quantum computing experiments

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Re: How GPT‑5.6 Sol helps run quantum computing experiments

#31

Post by qsera »

teiferer wrote: post #12
qsera wrote: post #9

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 m…

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. O…

>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.

Re: How GPT‑5.6 Sol helps run quantum computing experiments

#32

Post by philipallstar »

dgellow wrote: post #20
zarzavat wrote: post #16

Earlier quoted context omitted.

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?

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 a…

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?

Re: How GPT‑5.6 Sol helps run quantum computing experiments

#33

Post by Retro_Dev »

aurareturn wrote: post #23
crashprone wrote: post #13

Earlier quoted context omitted.

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.

Re: How GPT‑5.6 Sol helps run quantum computing experiments

#34

Post by carlailab2025 »

Leonard_of_Q wrote: post #27

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.

[dead]

Re: How GPT‑5.6 Sol helps run quantum computing experiments

#35

Post by MyMemoryfails »

zarzavat wrote: post #16
ForHackernews wrote: post #8

Earlier quoted context omitted.

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?

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.

Re: How GPT‑5.6 Sol helps run quantum computing experiments

#36

Post by aurareturn »

Retro_Dev wrote: post #33
aurareturn wrote: post #23

Earlier quoted context omitted.

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.

  Do you also have a graph for more useful metrics
Yes. I wrote about it in my original post.

  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?

Re: How GPT‑5.6 Sol helps run quantum computing experiments

#39

Post by Retro_Dev »

aurareturn wrote: post #36
Retro_Dev wrote: post #33

Earlier quoted context omitted.

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.

Do you also have a graph for more useful metrics Yes. I wrote about it in my original post. 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…

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.
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