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Arturo Nereu

ArturoNereu

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https://arturonereu.com

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posted an update about 1 month ago

I was not aware of the “Free Lunch Theorem” (Wolpert & Macready, 1990s), but it is a powerful idea. In a nutshell, if you average all the problems, every learning algorithm has the same performance. So if a model performs best for vision, it has to perform worse in something else. And another model has to perform worse in vision (or many). Seems this is the reason why DL/NNs dominate in language/vision tasks.

posted an update about 2 months ago

Finally, I’m reading "Deep Learning" by Ian Goodfellow et al. If you’d like more AI book recommendations, I’m saving my notes here: https://github.com/ArturoNereu/AI-Study-Group

posted an update about 2 months ago

I like the direction that Claude Code took in visualizing context usage. As these tools are being built, I think the work now needs to focus on control over how to clean up, inspect, and profile. Renderdoc-like maybe?

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