In large language models like ChatGPT, once the input has been processed and the model produces a final hidden vector - essentially a compact summary of everything seen so far - that vector must be converted back into actual words. This is done using an unembedding matrix, which maps the hidden vector back into the model’s vocabulary space. This unembedding matrix is effectively the transpose of the embedding matrix used at the start. It transforms the hidden vector into a set of raw scores, one
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ChatGPT, Claude, and Gemini aren’t intelligence. They’re large language models. The real power of AI isn’t chat or personality. It’s what happens when language gets connected to tools, workflows, permissions, and execution. That’s the layer most people aren’t looking at. Apple is positioned because they control devices and action. OpenAI wins if it escapes the chat box. Claude is aiming at enterprise workflows. Google is embedding AI into intent-heavy surfaces. Meta is betting on the social laye
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