"What do R2, laboratory error analysis, ensemble learning, meta-analysis, and financial portfolio risk all have in common? The answer is that they all depend on a fundamental principle of statistics that is not as widely known as it should be. Once this principle is understood, a lot of stuff starts to make more sense."
Read it!"Real-time machine learning is largely an infrastructure problem. Solving it will require the data science/ML team and the platform team to work together."
Read it!"So my take on Rich Sutton’s piece is that the lesson we should learn from the last seventy years of AI research is not at all that we should just use more computation and that always wins. "
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