Transcript
B (0:00)
Chatgpt is an LLM, right? It's a large language model. So is grok, so is perplexity. That's how these things work. It's really complicated. I'm not a data scientist, I'm not a programmer, but I do have a basic understanding of how this works. At its simplest, they are just next word predictors. They take information. When they are asked the question, one at a time, they are choosing the word that makes the most sense. We're going to play a little game. I'm going to put the phrase on the screen, and I want you to just blurt out the answer. So the dog runs fast. Most of you said fast. Not everybody. That's okay. Next question. Whoops. The soup is hot, hot, cold. Love it. Delicious. It's also a little Rorsack test, too, because I do this a lot and people will be like, you know, disgusting or something like that. And you're just like, okay, all right, one fish, two fish, red fish, blue fish. All right, we are all acting as LLMs right now. We are next word predictors. That, at a very simple level, is what ChatGPT is doing. Okay? That is what ChatGPT is doing. One more. The best Italian restaurant in Charlotte. Isolo. I like it. Okay, clearly, I don't know if there are any Italian restaurant owners here, but it's worth a lot of money if ChatGPT will answer that question the way you want it to. Right? You guys see where I'm going with this? Making sense.
A (1:34)
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