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Normal LLMs store knowledge in high-precision weights causing huge memory

This is insane, here’s how this works: Normal LLMs (like Grok or GPT variants) store their "kn0wledge" in billions of numbers (weights) Each weight is usually a high-precision decimal (like 3.14159), stored using 16 bits per weight. This makes the model huge in memory and

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