<ul><li>Deep learning, such as LLMs, understand reality through compaction and extraction of essence from data.</li><li>LLMs tend to adopt the true mechanistic understanding when presented with sufficient data.</li><li>Neural networks like deep learning systems learn the deepest rules and essence of mechanisms rather than memorizing every combination of data.</li><li>LLMs are proficient at tasks like detecting irony by checking for opposite outcomes to goals, showing they follow an equivalence to the underlying mechanisms.</li></ul>

LLMs do understand what underlies reality. How? And why not perfectly?

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