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174 points Philpax | 3 comments | | HN request time: 0.207s | source
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codingwagie ◴[] No.43719845[source]
I just used o3 to design a distributed scheduler that scales to 1M+ sxchedules a day. It was perfect, and did better than two weeks of thought around the best way to build this.
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1. davidsainez ◴[] No.43720086[source]
While impressive, I'm not convinced that improved performance on tasks of this nature are indicative of progress toward AGI. Building a scheduler is a well studied problem space. Something like the ARC benchmark is much more indicative of progress toward true AGI, but probably still insufficient.
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2. codingwagie ◴[] No.43720972[source]
the other models failed at this miserably. There were also specific technical requirements I gave it related to my tech stack
3. fragmede ◴[] No.43721178[source]
The point is that AGI is the wrong bar to be aiming for. LLMs are sufficiently useful at their current state that even if it does take us 30 years to get to AGI, even just incremental improvements from now until then, they'll still be useful enough to provide value to users/customers for some companies to win big. VC funding will run out and some companies won't make it, but some of them will, to the delight of their investors. AGI when? is an interesting question, but might just be academic. we have self driving cars, weight loss drugs that work, reusable rockets, and useful computer AI. We're living in the future, man, and robot maids are just around the corner.