supervised learning just learns input, output, or A to B mappings. On one hand, input, output A to B seems quite limiting. But when you find the right application scenario, this turns out to be incredibly valuable
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Unknown titles in the calls generative AI for everyone. At the heart of LLMs though, is this technology that learns from a lot of data to predict what is the next word using supervised learning. In summary, <span>supervised learning just learns input, output, or A to B mappings. On one hand, input, output A to B seems quite limiting. But when you find the right application scenario, this turns out to be incredibly valuable. Now, the idea of supervised learning has been around for many decades, but it's really taken off in the last few years. Why is this? When my friends asked me, hey, Andrew, why is super Summary
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