Have you interacted with Fable? It scored on ARC AGI 3 and is pretty dang impressive at everything I’ve thrown at it. They’re solving problems humans haven’t. They’re just senile. Also is calling something “arguable” really an assertion? More of a headscratcher than a real question, I suppose.
is calling something “arguable” really an assertion?
Yes. “Arguably unicorns exist” is me asserting there exist legitimate arguments for unicorns existing. By saying it this way I get to imply they exist without having to provide any real arguments myself, and if anyone attacks my position I can fall back to “I’m not saying they do exist, just implying there are other people who think they exist without providing any sources or arguments actually supporting that claim.”
I’m guessing we have different definitions of “solving” and “humans haven’t”.
I’ve never seen any evidence that LLMs can extrapolate into truly novel problem spaces. Can problems be “solved” though interpolation? Sure but not likely novel ones.
I notice here the distinction between “haven’t” vs. “can’t”.
Claiming that LLMs can be useful in solving some problems that humans simply haven’t bothered to spend time looking at more deeply is one thing, but turning around and using those solutions - which may genuinely be low-key exciting and even useful for some practical purposes - is not the same thing as representing evidence that the LLM has reached AGI status, let alone being up to the “very stable senile genius” level.
Apples to oranges, except I note that where hype was needed for profits, somehow statements that vaguely look correct (if you don’t delve too deeply) were found and provided. i.e., LLMs might not have reached the level of intelligence of an actual mathematical genius, senile or otherwise, but perhaps it has reached the intelligence level of an average techbro⁉️ (who again only values the appearance of correctness and doesn’t let little things like “facts” get in the way of their statements!)
I’m not going to keep doing this because I honestly don’t care if you want to be wrong. I’ve been writing these comments for other people who are going to read this thread and are interested the topic.
You obviously are not interested in taking these kinds of things seriously so just keep posting ads if you really want.
Okay I’m sorry to say this but you literally don’t know what you’re talking about if you don’t think that six months is a massive time frame right now. You are equating Gemini 3 to Mythos. It’s not comparable. You should actually do some research into this, since you seem to be so sure of yourself, what’s the harm!
Here’s an article from the smithsonian, if that helps. About the last round of AI math developments. Which was in July. So, yes, your video about something entirely different from six months ago is not actually very pertinent to the discussion?
Okay I’m sorry to say this but you literally don’t know what you’re talking about if you don’t think that six months is a massive time frame right now
I know it’s not because I do know what I’m talking about.
I’ve been hearing tech bros like you echo this same argument since GPT3 came out.
I promise you I’m very up to date on the state of the art.
You are equating Gemini 3 to Mythos
No, my original article was about GPT5.6 and you are talking about Fabel. Mythos likely doesnt even exist.
You are (willfully?) missing the point by refusing to engage with the concept being illustrated in the article. It doesn’t matter that it’s not 2 days old. The point is that these are not novel problems and AI is not solving them in the way you think it is.
The challenges here have been about the time it would take a human to solve the problem not the technical difficulty involved in solving the problem.
LOL. That’s quite a bold assertion.
Have you interacted with Fable? It scored on ARC AGI 3 and is pretty dang impressive at everything I’ve thrown at it. They’re solving problems humans haven’t. They’re just senile. Also is calling something “arguable” really an assertion? More of a headscratcher than a real question, I suppose.
Yes. “Arguably unicorns exist” is me asserting there exist legitimate arguments for unicorns existing. By saying it this way I get to imply they exist without having to provide any real arguments myself, and if anyone attacks my position I can fall back to “I’m not saying they do exist, just implying there are other people who think they exist without providing any sources or arguments actually supporting that claim.”
That says a lot more about you than it says about LLM’s
Citation needed.
I’m guessing we have different definitions of “solving” and “humans haven’t”.
I’ve never seen any evidence that LLMs can extrapolate into truly novel problem spaces. Can problems be “solved” though interpolation? Sure but not likely novel ones.
Techbros always exaggerate the claims.
I notice here the distinction between “haven’t” vs. “can’t”.
Claiming that LLMs can be useful in solving some problems that humans simply haven’t bothered to spend time looking at more deeply is one thing, but turning around and using those solutions - which may genuinely be low-key exciting and even useful for some practical purposes - is not the same thing as representing evidence that the LLM has reached AGI status, let alone being up to the “
very stablesenile genius” level.Apples to oranges, except I note that where hype was needed for profits, somehow statements that vaguely look correct (if you don’t delve too deeply) were found and provided. i.e., LLMs might not have reached the level of intelligence of an actual mathematical genius, senile or otherwise, but perhaps it has reached the intelligence level of an average techbro⁉️ (who again only values the appearance of correctness and doesn’t let little things like “facts” get in the way of their statements!)
Oh the frontier models definitely can, now.
https://www.indiatoday.in/technology/news/story/openai-says-its-unreleased-astra-model-solved-10-hard-math-problems-anthropic-claims-fable-cracked-5-2962067-2026-08-03
These are not novel problems, this isn’t a real source and this has nothing to do with AGI.
Literally starts with “OpenAI says” lol
If you want to learn more about what’s really going on here:
https://sciencereader.com/ai-mathematics-breakthrough-hossenfelder/
I was with you until you referenced Sabine Hossenfelder. She is no longer any kind of trustworthy source.
January 2026
Your video is ancient in this context. It does not reference any of this, actually.
You have a very hype driven view of how fast things are moving.
https://www.ibm.com/think/news/ai-cracked-jacobian-conjecture-humans-called-play
I’m not going to keep doing this because I honestly don’t care if you want to be wrong. I’ve been writing these comments for other people who are going to read this thread and are interested the topic.
You obviously are not interested in taking these kinds of things seriously so just keep posting ads if you really want.
Okay I’m sorry to say this but you literally don’t know what you’re talking about if you don’t think that six months is a massive time frame right now. You are equating Gemini 3 to Mythos. It’s not comparable. You should actually do some research into this, since you seem to be so sure of yourself, what’s the harm!
Here’s an article from the smithsonian, if that helps. About the last round of AI math developments. Which was in July. So, yes, your video about something entirely different from six months ago is not actually very pertinent to the discussion?
https://www.smithsonianmag.com/smart-news/ai-disproves-a-decades-old-mathematical-idea-the-biggest-conjecture-that-the-tech-has-played-a-role-in-yet-180989189/
I know it’s not because I do know what I’m talking about.
I’ve been hearing tech bros like you echo this same argument since GPT3 came out.
I promise you I’m very up to date on the state of the art.
No, my original article was about GPT5.6 and you are talking about Fabel. Mythos likely doesnt even exist.
You are (willfully?) missing the point by refusing to engage with the concept being illustrated in the article. It doesn’t matter that it’s not 2 days old. The point is that these are not novel problems and AI is not solving them in the way you think it is.
The challenges here have been about the time it would take a human to solve the problem not the technical difficulty involved in solving the problem.