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Joined 6 months ago
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Cake day: May 11th, 2024

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  • I think it’s more likely a compound sigmoid (don’t Google that). LLMs are composed of distinct technologies working together. As we’ve reached the inflection point of the scaling for one, we’ve pivoted implementations to get back on track. Notably, context windows are no longer an issue. But the most recent pivot came just this week, allowing for a huge jump in performance. There are more promising stepping stones coming into view. Is the exponential curve just a series of sigmoids stacked too close together? In any case, the article’s correct - just adding more compute to the same exact implementation hasn’t enabled scaling exponentially.









  • The “caravan” of scary South American migrants that Trump fear-mongered about back in '15 (Jesus, has it been a decade?), they were largely subsistence farmers that were forced off of their lands by multi-year droughts that were demonstrably an effect of climate change. In just the last few years, it’s almost comical how dramatically present the effects of climate change are. Whether or not we’re able to admit it to ourselves consciously, I think everyone feels it. We’re about to hit a dozen different asymptotes, and we’re clearly not ready. So, turns out, fear-mongering is a particularly successful strategy in this kind of zeitgeist.









  • When I was a little girl I thought that everything, all the abuse and neglect, it somehow made me… special. And I decided that one day I would write something that would make little girls like me feel less alone. And if I can’t write that book…

    …if I don’t, that means that all the damage I got isn’t good damage, it’s just damage. I have gotten nothing out of it, and all those years I was miserable was for nothing. I could’ve been happy this whole time and written books about girl detectives and been cheerful and popular and had good parents, is that what you’re saying? What was it all for? - Diane Nguyen, BoJack Horseman, S06E10, “Good Damage”