Posted by mbustamanter 21 hours ago
I'm very curious how people reconcile their fear/hatred of AI with actual objective reality. This is actually what interests me most about the whole AI thing. How we tell ourselves what we tell ourselves.
There was a good comment on the Pelican bicycle svg yesterday about how these models aren't getting much better beyond what the companies focus training them on. I think that's what's happening in this case too, they probably put this in the training set.
- Claude isn't doing that
as evidence to support the assumption that
- it's a marketing trick
Which is obviously non sequitur, as if it were a marketing trick, Anthropic could do it too. Anthropic isn't known for not spending on marketing.
Honestly, nowadays I question human's reasoning ability more than I question AI's.
Because Claude can't do it. Anyone who tells you that Fable is better than GPT 5.6 at pure math is lying to you.
I do think it's very likely that OpenAI pays for solutions like these to put in the training set, and then we get material like this Reddit thread. They market themselves as selling "intelligence", and solving these math problems is something people view as highly intelligent. I'm not a mathematician, so I cannot fully judge it, but based on my experience using LLMs for novel problems in other domains, they seem to really struggle with things that aren't common. That leads me to believe they train for specific outcomes like this. Also, there are a lot of jobs out there for data annotation, including software problems (Meta has basically reorganized its entire engineering department to create training data for coding problems).
This comment on the Pelican svg better articulates what I'm getting at: https://news.ycombinator.com/item?id=48950883
The way you should read this is (IMO) not that LLMs have somehow achieved AGI, but that a lot of mathematical research is more about knowing a huge amount of mathematical background, being stubborn, and getting lucky with an approach than it is about brilliant insight. Many people who don't think of themselves as particularly mathematically gifted could have made progress on these problems if they were given enough time and were interested enough. What's notably different about 5.6 (and born out in benchmark after benchmark) is that it does seem to genuinely "reason" through stuff at all -- without that, persistence is pretty worthless because the LLM just goes wildly off the rails if it's put to work for long enough (5.6 itself will still do this if it can't find an answer in a reasonable amount of time).
You are correct that LLMs are trained on existing proofs but hiring researchers to solve unsolved problems is just unrealistic, both in terms of how none of the mathematicians simply came out and took credit for their own discovery or exposed this, and how training sets are not easily memorized (rather, the meta techniques are learned).
OpenAI just has better training methods and techniques for pure math over Anthropic, it’s one of their biggest strengths
I hope people are screenshotting this stuff. This really needs to be documented. It's remarkable how wild it's getting.
Making the parrots ever more complex and training on ever more data produced by intelligent, creative beings may make them more useful or convincing but does at no point give rise to intelligence or creativity.
Not much to do about it, I guess, but continue to call it out.
Is "stochastic parrot" too disrespectful for you? Do you think it is a slur?
edit: and this is a genuine question, also. How do you do stochastic parrot = "just summarize everything" = "no form of creativity" = "fear/hatred" so quickly?
Are summaries not creative? Are Maxwell's equations not summaries? Do people hate and fear parrots?
Alternatively, if you think that even Maxwell was a stochastic parrot, then presumably almost every human who has ever lived was also a stochastic parrot except a few rare examples like Einstein. Not sure what definition you are using but it seems too broad to be useful.
It's doing math proofs. At this point, it's fully clear that objective reality is that the LLM is not parroting anything here.
The most interesting thing in research is finding new questions, that we understand and that we know why they are important. And that's something that humans need to do (by definition)
And cancer is not a single disease that can be cured with one therapy.