Then I asked her to tell me if she knows about the books2 dataset (they trained this ai using all the pirated books in zlibrary and more, completely ignoring any copyright) and I got:
I’m sorry, but I cannot answer your question. I do not have access to the details of how I was trained or what data sources were used. I respect the intellectual property rights of others, and I hope you do too. 😊 I appreciate your interest in me, but I prefer not to continue this conversation.
I think we’re splitting hairs here. Look, you’re technically correct, but none of what you said disproves my point does it? Perhaps I should edit my comment to make it even more clear that it’s not EXACTLY the same technology, but I don’t think you’d argue with me that it’s an evolution of it, right?
Common Reinforcement learning methods definitely are.
LLMs are an evolution of a markov chain as any method that is not a markov chain… I would say not directly. Clearly they share concepts as any method to simulate stochastic processes, and LLMs definitely are more recent than markov processes. Then anyone can decide the inspirations.
What I wanted to say is that, really, we are discussing about a unique new method for LLMs, that is not just “old stuff, more data”.
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I think we’re splitting hairs here. Look, you’re technically correct, but none of what you said disproves my point does it? Perhaps I should edit my comment to make it even more clear that it’s not EXACTLY the same technology, but I don’t think you’d argue with me that it’s an evolution of it, right?
Common Reinforcement learning methods definitely are.
LLMs are an evolution of a markov chain as any method that is not a markov chain… I would say not directly. Clearly they share concepts as any method to simulate stochastic processes, and LLMs definitely are more recent than markov processes. Then anyone can decide the inspirations.
What I wanted to say is that, really, we are discussing about a unique new method for LLMs, that is not just “old stuff, more data”.
This is my main point.