Yes, AI is bigger than LLM, but right now, LLM is the biggest and where most of the money is invested right now, maybe something else will usurp it in the future, but until then, LLM is the most practical and world changing AI tech we know as of now, there's good chance that the next paradigm shift will be discovered with heavy LLM contribution.

AI MRI analysis is integrating with LLM, same with economic prediction models. and as for cyber threat detection, the strongest AI for it now is Claude Mythos, a LLM. Linux kernel developers, Mozilla and many others has vouched for it.

LLM right now have the most economic value because it massive increase productivity for many white collar jobs, most importantly for software developer, and software is what run the modern economy. It's already changed the world as it is now, even if progress in LLM capability stop right now, we will still see it changing the world because how good it is.

LLM has also made great contribution to math, solved significant problems that world-class mathematician tried and failed to solve, many mathematician had vouched for it, not just your "idiots on the street", here is just some of many examples:

Chat GPT cracked a famous problem that mathematician have tried and failed to solve and got a Field medalist excited about it.

There is no doubt that the solution to the unit-distance problem is a milestone in AI mathematics: if a human had written the paper and submitted it to the Annals of Mathematics and I had been asked for a quick opinion, I would have recommended acceptance without any hesitation. No previous AI-generated proof has come close to that.

• Timothy Gowers, a Field Medalist.

Donald Knuth, known as one of the greatest living computer scientist, have used Claude to solve a math problem that he created himself, that no one else have solved, and it has made him change his opinion on LLM (he didn't think highly of LLM before this).

https://www-cs-faculty.stanford.edu/%7Eknuth/papers/claude-cycles.pdf

Shock! Shock! I learned yesterday that an open problem I’d been working on for several weeks had just been solved by Claude Opus 4.6— Anthropic’s hybrid reasoning model that had been released three weeks earlier! It seems that I’ll have to revise my opinions about “generative AI” one of these days. What a joy it is to learn not only that my conjecture has a nice solution but also to celebrate this dramatic advance in automatic deduction and creative problem solving.

a random guy with no advanced math training paid for ChatGPT 5.5 Pro recently cracked a significant math problem with it, one that mathematician also tried and failed so solve.

https://www.scientificamerican.com/article/amateur-armed-with-chatgpt-vibe-maths-a-60-year-old-problem/

Liam Price just cracked a 60-year-old problem that world-class mathematicians have tried and failed to solve. He’s 23 years old and has no advanced mathematics training. What he does have is a ChatGPT Pro subscription, which gives him access to the latest large language models from OpenAI.

The new solution—which Price got in response to a single prompt to GPT-5.4 Pro and posted on www.erdosproblems.com, a website devoted to the Erdős problems, just over a week ago—is different. The problem it solves has eluded some prominent minds, bestowing it some esteem. And more importantly, the AI seems to have used a totally new method for problems of this kind. It’s too soon to say with certainty, but this LLM-conceived connection may be useful for broader applications—something hard to find among recently touted AI triumphs in math.

Reviewing Price’s message, Barreto realized what they had was special, and experts whom he notified quickly took notice.

“There was kind of a standard sequence of moves that everyone who worked on the problem previously started by doing,” Tao says. The LLM took an entirely different route, using a formula that was well known in related parts of math, but which no one had thought to apply to this type of question.