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Joined 2 years ago
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Cake day: July 30th, 2023

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  • Reminds me of a thread I saw here a while ago on “What if advertising were illegal?”

    I’ve found the best method for reducing my need on Amazon is to just buy less crap. Online shopping is simple because you can get stuff immediately, but I don’t think anybody “needs” 3-4 new products per week.

    Aside from that, I try and support local: find local shops that sell items similar to my style, or trust word of mouth for online retailers that are good. At the end of the day, as long as you’re buying good-quality stuff (which oddly seems to spend less on advertisements) it doesn’t really matter where exactly you buy from, as it’s all pretty similar in price / quality.











  • Another great example (from DeepMind) is AlphaFold. Because there’s relatively little amounts of data on protein structures (only 175k in the PDB), you can’t really build a model that requires millions or billions of structures. Coupled with the fact that getting the structure of a new protein in the lab is really hard, and that most proteins are highly synonymous (you share about 60% of your genes with a banana).

    So the researchers generated a bunch of “plausible yet never seen in nature” protein structures (that their model thought were high quality) and used them for training.

    Granted, even though AlphaFold has made incredible progress, it still hasn’t been able to show any biological breakthroughs (e.g. 80% accuracy is much better than the 60% accuracy we were at 10 years ago, but still not nearly where we really need to be).

    Image models, on the other hand, are quite sophisticated, and many of them can “beat” humans or look “more natural” than an actual photograph. Trying to eek the final 0.01% out of a 99.9% accurate model is when the model collapse happens–the model starts to learn from the “nearly accurate to the human eye but containing unseen flaws” images.