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To me, the analogy breaks down before it begins: firstly, LLMs don’t merely blur, but perform highly non-linear transformations, which means you can’t just squint and get a sense of the original; secondly, for the photocopier, the error is a bug, whereas, for LLMs, all errors are features. Let me explain. Remember the context.
For a detailed overview of predictive AI techniques, please refer to Chapter 4 of my book The Art of AIProductManagement. Navigating the LLM triad While predictive models trained from scratch can excel at very specific tasks, they are also rigid and will refuse to perform any other task.
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