Q What does it look like when somebody sells someone?
A Well, I mean, there's a technical reason. These are LMs are probabilistic. They're not precise. The, the value of LLM is when it's essentially in an ontology wrapper, because to, to, to actually create value, you have to be able to take the output, serialize it and deserialize it in the context of the business. So the logic actions and security of the business and its tribal knowledge and what it's trying to accomplish. LLMs are vertically crucial, but the, but, but the error bound is very, very, very narrow. And the way you actually do LLMs in the real world, not in theory, not as like, Is that you essentially put them in a concatenated chain where each single thing has to be done as a street unit, because otherwise the underlying math is 95 times a hundred separate change. It's like totally unreliable. And if you do it any other way, you're getting a steak dinner and that steak dinner is super tasty. It's not going to work. And even worse than the steak dinner, honestly, is that you're being taught how to do something incorrectly. It's like, it's like, okay, I'm going to learn how to learn From a wokester.
AI assessment note: “Well, I mean, there's a technical reason. These are LMs are probabilistic.”