LLMs Are Still Toxic, Stuck in the Past, and Bad at Math

ekjhgkejhgk

LLMs are bad at math? Sorry, I'd rather take the opinion of Terrence Tao than that of some rando on the internet. https://terrytao.wordpress.com/2026/07/21/a-digestion-of-the... https://chatgpt.com/share/6a5fdc7a-d6f8-83e8-bbea-8deb42cfed...

imglorp

Arithmetic and symbolic math are not the same skills. Anyway it seems to have gotten past its Dyscalculia. > what is 126347832164398 * 127430123748901234 > Compute large integer multiplication precisely 16,100,519,888,114,640,782,096,553,067,132

saberience

Is there a term for bloggers who try to get attention by participating in this sort of dated, inaccurate "AI doomerism"? The idea that AIs are "bad at math" because if you send it 100s of basic arithmetic questions, it can get one wrong, is frankly laughable. It's like me saying Terence Tao is bad at math because I sent him 100 long division problems and he made a mistake in one. Yes, we know models think in tokens, and if you give it a bunch of math problems (and its not using tools like Python to deterministically work on the problems) then of course you cannot guarantee accuracy. But no one thought tool-less LLM calls were a solution for arithmetic in the first place. So the author is constructing a great big straw-man and attacking it vigorously. The reality is this, the frontier models are as good as (OR BETTER THAN) the leading mathematicians in the world right now. Leading mathemeticians (like Terence Tao) are using Fable and GPT5.6 as partners in doing research. As for being stuck in past? Again, weird Anti AI/AI Doomerism because models have fixed weights. So what? They can use tools (and do so very well) if they need up to date data and information. Again it's like the author wants to paint a picture, based on their own biased beliefs and chooses to represent the current state of AI in an entirely inaccurate fashion.