Starting with a surprisingly small number of high-quality examples can effectively train AI, as demonstrated by the transition from needing thousands of data points to just ten. The initial assumption of requiring vast amounts of data shifts to recognizing that a small, refined dataset from top creators can serve as a powerful foundation. This approach emphasizes the importance of aspiration in AI performance, aiming for it to surpass human capabilities. Additionally, capturing the chain of thought in data is crucial, as it is often missing in broad datasets available on the internet.

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