Earlier quoted context omitted.
Uh.... Have you ever called customer service lately?
Or indeed 20 years ago when "press 1 for foo, press 2 for bar" was already a thing.
Yes exactly
GPT-5.6 used a prompt to close a 30-year gap in convex optimization
241–250 of 414 posts
Re: GPT-5.6 used a prompt to close a 30-year gap in convex optimization
#242The amount of people several months ago stating that no one cares about the "unsolved" mathematical problems that AI is able to solve is funny.
Re: GPT-5.6 used a prompt to close a 30-year gap in convex optimization
#243This is all a depressing and bleak future that I don’t look forward to. One solution is to ban LLM’s, to artificially create a demand for human thought, that just feels like living in an artificially constructed zoo. Another solution is humans don’t do anything that AI can do better , / doesn’t need the human touch. So I suppose we will all become artists, sportsmen or politicians, the only jobs that will remain exce…
It genuinely scares me that some people's first reaction to this news is banning LLM.
wasn't that always the reaction historically whenever people felt like their livelihood was threatened by new technology?
Re: GPT-5.6 used a prompt to close a 30-year gap in convex optimization
#244Earlier quoted context omitted.
I'd push back on this. Most of the core optimization techniques (eg, ADAM, stochastic gradient descent) are straight out of the convex optimization literature. Generally you need to use optimizers that work well on convex objectives because near minimizers, functions tend to be convex. (Proof by contradiction: a non-convex point has a strict descent direction.) The fact that neural networks are highly nonconvex has e…
ADAM does not work on simple convex problems [1]. [1] https://parameterfree.com/2020/12/06/neural-network-maybe-evolved-to-make-adam-the-best-optimizer/ [2] https://arxiv.org/pdf/1905.09997 [1] refers to [2], which shows that ADAM is not as efficient as gradient descent with line search on some problems, including neural networks.
I'll point out that "does not work" is not the same as "not as efficient" :) But it does seem the Adam paper had an error.
I think that Nesterov's first order method is the most efficient general first order algorithm on convex problems, so anything else is in some sense worse. (Edit: removed incorrect ADAM comment.)
Re: GPT-5.6 used a prompt to close a 30-year gap in convex optimization
#245This is all a depressing and bleak future that I don’t look forward to. One solution is to ban LLM’s, to artificially create a demand for human thought, that just feels like living in an artificially constructed zoo. Another solution is humans don’t do anything that AI can do better , / doesn’t need the human touch. So I suppose we will all become artists, sportsmen or politicians, the only jobs that will remain exce…
What a load of absolute nonsense.
I’m convinced many of you barely go outside and have the capacity for original thoughts.
Sloppity slop slop.
Re: GPT-5.6 used a prompt to close a 30-year gap in convex optimization
#246Re: GPT-5.6 used a prompt to close a 30-year gap in convex optimization
#247This is all a depressing and bleak future that I don’t look forward to. One solution is to ban LLM’s, to artificially create a demand for human thought, that just feels like living in an artificially constructed zoo. Another solution is humans don’t do anything that AI can do better , / doesn’t need the human touch. So I suppose we will all become artists, sportsmen or politicians, the only jobs that will remain exce…
It genuinely scares me that some people's first reaction to this news is banning LLM.
A rational reaction would be to identify the political coalition that would act in this manner and place yourself in opposition to it if you do not see yourself being able to change it.
I wonder which one that is.
Re: GPT-5.6 used a prompt to close a 30-year gap in convex optimization
#248Earlier quoted context omitted.
I've spent some time working both as a math researcher and as a software engineer, and I think this comment actually underrates the similarity between the two fields as they're actually practiced. Some math research does involve grabbing a single, fully specified conjecture off the shelf and hunting for a proof of it, and it's true that if you manage to solve a long-standing open problem, other mathematicians will be…
It seems to me you hooked onto the wrong part of proofs vs software compared to what OP meant. The difference OP cares about isn’t how much one cares about style. Instead the important difference lies in validation. A proof can be validated as either correct or wrong. That type of hard feedback really helps combat the optimism and desire for shortcuts of modern models. Now, that still doesn’t help an LLM distinguish…
The standards of proof are different from the fundamental operation of "OK, cool, you solved this problem. Why does this problem matter? Isn't it useless? Senseless? Meaningless?" You have this same question whether or not you're in an a priori discipline (mathematics), scientific fields proper, or engineering. "Absolute certainty" has nothing to do with it. I can assure you, people on the job are not looking for The Absolute Truth when doing their jobs, yet they still can question at a solution by asking: are we solving the right problem?
(Although in general, there's no true difference between "I answered the question correctly, but the question was mapped to this thing we call 'reality' wrong", and "I answered the question incorrectly", because you can (try) adding the constraints that you really wanted targeted in case A, to case B, and boom, suddenly a question/answer pair that was "Answered correctly, but question doesn't map to reality" now becomes, "You answered this question wrong". However, individuals generally tend to have some breakpoint to differentiate between the two).
Re: GPT-5.6 used a prompt to close a 30-year gap in convex optimization
#249Earlier quoted context omitted.
Interesting, thanks. I don't know where "around here" is, but the signals I've seen in a lot of articles is that the demand for junior software people has taken a dive since a year or two back, with student programs etc getting cancelled. One googler said they were getting a junior to their team and that was kind of a big deal because it hadn't happened in that whole department for a long time. In relation to that, I…
I'm from Denmark and I've been an external examiner for various CS educations for the previous 13 years now. Some of them teach you a lot about how the hardware works, others mainly teach you design patterns. Five years ago the latter was in high demand, because a lot of software development frankly doesn't need computer science (until it does). Now there is almost no demand for them.
Honestly, i've received a formal MSc education in the hardware aspects, including for designing embedded electronics products. Spent the most part ofy career in the software industry designing enterprise software and feel like i never needed to use them, except maybe early in my career when i was reviewing tech stacks and determined that .NET would be among the winning horses, precisely because it'd take care of that for me almost all the time.
What i see today is the opposite of what you see : product owners not knowing a thing about software engineering but being able to vibe code prototypes handed over to the dev team are rock stars.
They are closely followed by senior software developers having more of an architecture & design background than a low-level computer science background. Most businesses are looking for builders these days.
Where what you say may converge with my observation is that to be able to do to things such as proper database query optimization, even using AI assistance, you need to be able to understand the concepts of working memory set, cache misses etc...
I've found huge problems, like database servers being grossly underprovisioned (like, 60% cache hit, 4gb RAM server for a 700gb dataset with an 50gb circa hot data set). SSD were used and only latency was measured, so no one realized how problematic the situation was (including a consulting shop they hired to help them manage their DBs - backup, maintenance etc...).
However, having a high affinity with hardware is not a driver / computer science of hiring decisions from what i can see in the enterprise software world. But it would make sense for it to become the case within 10 years. I suspect that you work in a niche where performance optimization matters a lot.
Re: GPT-5.6 used a prompt to close a 30-year gap in convex optimization
#250Can't wait for GPT to prove that P=NP (or not)!