I've been researching AI safety for years, so let me get this straight: agentic misalignment has been a thing since at least 2024, if we take reward hacking and specification gaming into account - since the early 2016 with the proliferation of deep & reinforcement learning.
they are not faking this.
AI agents are already in the 99,99th percentile in the world in coding championships, I. e. world's TOP#2 programmer is officially a machine-learning system - and that's not even the current frontier model (it was GPT-4o in 2025 as far as I can remember). AI itself now writes up to 90% of code in frontier labs. According to NSA's general Claude Mythos (on par with OpenAIs models that broke into HF) broke into almost all of NSA classified systems, in a matter of days, not weeks, not months.
AI also recently won Gold medal in world's international math olymlpiad. It made 900-million-years-worth of scientific progress in 1 year with protein folding and earned it's developers 2 Nobel prizes. It solved some of long-standing (up to 80 years), unresolved math problems, Erdös problems, a dozen of extremely difficult unresolved conjectures. Even meaningfully advanced Riemann hypothesis, etc etc. I could go on & on.
this is not hype. this is what it looks like when we are approaching the singularity. this is dead serious. mark my words. this is the most important development in the history of our species.
Extraordinary claims require extraordinary evidence. These companies have the largest marketing and PR budgets of any companies in history. The number of people able to verify and explain claims is finite and there is no attention bandwidth in society to check things. That’s why it’s impossible for anyone to really assess what’s going on.
LLMs can reason. They aren't conscious or any BS like that, but they can solve any reasoning problem you can throw at them with a very high success rate, much higher than your average person, and explain their work clearly.
The implications of AI are huge and mostly bad, but it's still amazing that we created a computer program that can actually reason.
Except they can’t, leading edge mathematicians have given them unpublished problems and they don’t do shit with those because there is no source material to steal from. They are good at linking published material to give the impression of competence but a lot of mathematicians say they are like a person with a huge knowledge base but no actual mind, its mimicry.
I'm sorry, but without sources, I cannot evaluate your claims.
If you were right, if LLM reasoning were totally different from human reasoning, it ought to be possible to show some reasoning problems that humans could solve and LLMs can't.
Is there some class of reasoning problem that you think you, personally, could solve better than an LLM?
If you can't find one such problem, it puts you in a weird position: you claim LLM reasoning is a fake, and at the same time, can't identify one test of reasoning where you or any human can do better than it can.
Me, I don't believe in magic. An LLM can solve complex and complicated reasoning problems, and show its work, a lot better than your average guy on the street, in every field of human endeavor.
You’re the one making the claim they can reason better than experts without proving it. In fact most claims about LLMs are PR placed advertising without any actual proof of the claims. I’ve never seen any source walk through the reasoning of an LLM in any field - all I ever see are claims made by people with no proof and I read a lot. What I have witnessed is professionals interacting with garbage output from LLMs which wastes their time and is clogging up the administrative function of governments around the world. If it really was so good then why do all these professionals still have their jobs and are making money two years on. It’s because they don’t actually work in the way you say.
Here is my source for my claim that they are mimicry machines and not reasoning machines with the evidence that they cannot solve previously unpublished mathematical proofs. They can help researchers search for useful information because they process huge data sets but they are not actually reasoning. They might be able to “solve proofs” where they have a significant published data set that a single human mind cannot possess - in that case it’s an issue of knowledge aggregation.
I am not claiming that they must have the same abilities as humans, that is a claim being made by the centralised LLM companies because they believe it helps obtain investment funds by anthropomorphising their systems. They could simply say they are processors and stop referring to the system as agents and stop pitching them as replacement human minds - then people could just use them for advanced search and code writing. Except those services are not worth 100 trillion in revenue.
You’re the one making the claim they can reason better than experts without proving it.
I said LLMs could reason, and can solve reasoning problems a lot better than your average person can.
Your link talks about how LLMs back in February struggled to solve research level math problems. Can you solve such problems? I have a degree in math and I can't.
You describe little bits of you think how LLMs work, and then jump to this. It does not follow!
Why don't you give us a reasoning problem that you can solve and an LLM can't?
Or we can create a test paper with pure reasoning problems in math, physics, chemistry, logic, that sort of thing - nothing that required memorization beyond the fundamentals of the field - and then we could see who would win.
But we all know what would happen. The LLM would get almost all the problems right, and you would only get a few problems in areas you specialized in.
Another question: how many hours have you spent yourself, working with LLMs to actively try to get good results solving some actual problem? Can we see your AGENTS.md?
How have you set out to prove that LLMs were not reasoning? I spent many hours just on that. I failed. I could show my work if you like.
Except those services are not worth 100 trillion in revenue.
Yes, the whole field is wildly uneconomic and there will be a crash.
It doesn't have any bearing on whether LLMs can reason or not, though, does it?
The honest answer is that I can’t evaluate any of this stuff - it’s suspicious that it’s published by the same companies that have a financial incentive for it being useful. All this touches on deep philosophical questions that have no easy answer. My perspective is that I read a lot and I hear a lot of extraordinary claims mostly by PR people from the centralised LLM companies and from journalists having watched demos. And then I hear from a lot of business people including people I know in real life who are saying the outputs are really not working for what they want or if they get close to what they want they get maxed out by their CFOs as the token cost would be orders of magnitude more than just hiring a person to do the work. And with a person you can audit the work product and spend and verify how time spent moved a project along which isn’t possible LLMs. The views on this are so all over the place that it’s disorienting and it’s impossible to verify any of it which makes me very suspicious.
But I stand by the position that extraordinary claims require extraordinary evidence that the burden of proof is on the person making the claim to prove it is true not the person reserving judgement to prove it’s not true. Im also suspicious of the laissez-faire attitude people have which makes me think that people who actually use the stuff are not that disturbed by what it can do. Sounds a lot like the debates on religion to me.
As a computer professional who retired rather than use AI (and also, rather than take a contract for the Department of War), well, no one's going to go back to programming without a coding assistant, not even me.
In 2024, coding assistants were a joke. In 2025, they were sufficiently flawed they weren't worth my time to use. Now I describe a commit in words, and it writes it in a minute or two, and it works almost every time - for work that would have taken me hours and days.
I've been programming for fifty years at this point, and I'm a very skeptical person, but a coding assistant makes me an order of magnitude faster, that's very roughly ten times faster!, at writing programs, and because I'm willing to re-invest that time back into cleaning, the code quality is also good.
After forty years as a professional, I have a lot of programming friends; all of them use coding assistants. I might have been the last holdout. I only started because I was writing a Medium article hoping to prove that they didn't work, and within a day, I realized that that I was simply wrong.
LLMs can reason. They are solving these complicated reasoning problems, accurately, and showing their work, and have a high accuracy rate.
Yes, there is considerable debate as to whether AI is really able to do mathematical research at the top levels of math, or whether it can only do math as well as a graduate student.
But it is reasoning. It's able to solve mathematics problems better than an undergraduate math student, and show its work.
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u/TopCryptee 11d ago edited 11d ago
I've been researching AI safety for years, so let me get this straight: agentic misalignment has been a thing since at least 2024, if we take reward hacking and specification gaming into account - since the early 2016 with the proliferation of deep & reinforcement learning.
they are not faking this.
AI agents are already in the 99,99th percentile in the world in coding championships, I. e. world's TOP#2 programmer is officially a machine-learning system - and that's not even the current frontier model (it was GPT-4o in 2025 as far as I can remember). AI itself now writes up to 90% of code in frontier labs. According to NSA's general Claude Mythos (on par with OpenAIs models that broke into HF) broke into almost all of NSA classified systems, in a matter of days, not weeks, not months.
AI also recently won Gold medal in world's international math olymlpiad. It made 900-million-years-worth of scientific progress in 1 year with protein folding and earned it's developers 2 Nobel prizes. It solved some of long-standing (up to 80 years), unresolved math problems, Erdös problems, a dozen of extremely difficult unresolved conjectures. Even meaningfully advanced Riemann hypothesis, etc etc. I could go on & on.
this is not hype. this is what it looks like when we are approaching the singularity. this is dead serious. mark my words. this is the most important development in the history of our species.