I'm curious about how language models work. I know they're trained on massive amounts of data, but at the end of the day, they generate text that sounds human-like. Does this mean the model actually understands the logic behind sentences, or is it just regurgitating data it's seen before? Can someone explain?
How is text generation possible with deep learning?
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Hello, you've asked an interesting question. Essentially, these models learn patterns in the data, so what we call "understanding" isn't random—it's really just repetition in the data. So, in practice, which projects do you think you'd most use language models for?