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Joined 1 year ago
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Cake day: September 11th, 2023

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  • This is probably because of a lack of training data, where it is referencing only one example and that example just had a mistake in it.

    The one example could be flawless, but the output of an LLM is influenced by all of its input. 99.999% of that input is irrelevant to your situation, so of course it’s going to degenerate the output.

    What you (and everyone else) needs is a good search engine to find the needle in the haystack of human knowledge, you don’t need that haystack ground down to dust to give you a needle-shaped piece of crap with slightly more iron than average.


  • After almost 2 years, Roshan’s pit is back where it belongs. I think the pit switch is a good solution to the Pit Problem, but sticking those pits all the way in the corners made it really difficult to contest a Roshan attempt. You needed to commit pretty hard just to get there and then the terrain was pretty difficult to get a good Blink angle on too. Now we have it back in the middle of the map and it will be fun to see the dynamic plays around there. And I hope to see Roshan barreling through a team fight in the mid lane during TI 2025.






  • Torrents are already very hard to block. You don’t actually need a tracker, because all modern torrent clients support DHT (distributed hash table). You only need some way to get the initial hash for a torrent, so that’s where trackers are still useful, but once you’re connected to the swarm, you can only be blocked if the entire swarm is blocked.

    Tracking though… It’s too easy to get IP addresses for the entire swarm and I don’t see how you could ever fix that. Tor doesn’t really solve that issue either, it just moves it to places where you won’t get in legal trouble or to people who don’t mind getting in legal trouble, a bit like VPN providers.




  • I don’t think you even need the actual stuff to train a neural network to recognize it. For example, if I wanted to train a neural network to recognize pictures of lions, but I didn’t have any actual pictures of lions, I could use pictures of lion-shaped things, lion-colored things and locations where lions might appear. If a picture is hitting all three of those, it’s very likely to be a lion. Very likely is all a neural network can do, so it’s good enough for my purposes.