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3min chapter
Sara Hooker: Cohere For AI, the Hardware Lottery, and DL Tradeoffs
The Gradient: Perspectives on AI
Machine Learning
economics is about introducing enough assumptions to get the date o distribution into one way you can conceivably model it with a lineal model. In stark contrast to deepnor networks, where essentially you delegate representation to the model. I think what's wherte there's connections is at a lot of economics is focused on as both certainty and Uncertainty. And in machine learning we often ascribe a high uncertainty to both noisy points as well as a typical points.
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