No, you're wrong. The LLMs cannot do code and mathematics better than a human yet, and there are principled reasons to believe that our present methods won't scale to the point where they can. I'm a software engineer.. I now use LLM assistance heavily. It's not like working with a programmer who's better than me, it's like working with a bright intern who doesn't have good design sense yet but has memorized all of the manuals. LLMs can exceed the human capacity to assemble large masses of facts, but they are deficient in higher-level judgment and taste. I think this is because they are in one important way much simpler than a human mind. A human mind is a large society of specialized agents with different computational strengths and styles. This gives us the ability to attack problems from many different directions. An LLM really only really emulates one of the kinds of things a brain is good at - the kind of statistics-based inference that we seem to use when we are learning natural languages. It does that very well but ... ...because it doesn't have any of the other specialist subsystems that humans have in their brains, its way of engaging in the world is in a sense much narrower than a human's. I think it's fairly likely that we will build human-equivalent intelligences someday, and they will have LLMs as components. But they'll need to emulate the multimodal processing of a human brain, the complex but adaptive messiness produced by hundreds of millions of years of evolution. The LLMs aren't that, and can't be that. They're a step on the way, but they're nowhere near the end of the road.