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this post was submitted on 13 Aug 2023
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Technology
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Large language models literally do subspace projections on text to break it into contextual chunks, and then memorize the chunks. That's how they're defined.
Source: the paper that defined the transformer architecture and formulas for large language models, which has been cited in academic sources 85,000 times alone https://arxiv.org/abs/1706.03762
Hey, that comment's a bit off the mark. Transformers don't just memorize chunks of text, they're way more sophisticated than that. They use attention mechanisms to figure out what parts of the text are important and how they relate to each other. It's not about memorizing, it's about understanding patterns and relationships. The paper you linked doesn't say anything about these models just regurgitating information.
I believe your "They use attention mechanisms to figure out which parts of the text are important" is just a restatement of my "break it into contextual chunks", no?