This document discusses the importance of balancing multiple models when making predictions or decisions to avoid relying too heavily on any single approach. It recommends ensembling several models and examining their collective results to minimize individual errors and biases, leading to more well-rounded and accurate conclusions. Testing ideas across different techniques and perspectives can help achieve overall stability and reduce risks.

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17. Multiple models balance this out