Ryan, how do neural networks compensate for variances or gradations and experimentation….for
Craig Ellison

This is a really cool thought/question. My basic response to this is that the more data you feed a system, the more it will know. When discovering that the cup is hot you can tell a system to figure out more detail or to avoid. Both are fine responses to the input. One leads to learning more, the other leads to ensuring “safety.” Sounds a lot like the difference between people with high and low risk tolerances :).

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