• 6 Posts
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Joined 2 years ago
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Cake day: June 13th, 2023

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  • I think the main barriers are context length (useful context. GPT-4o has “128k context” but it’s mostly sensitive to the beginning and end of the context and blurry in the middle. This is consistent with other LLMs), and just data not really existing. How many large scale, well written, well maintained projects are really out there? Orders of magnitude less than there are examples of “how to split a string in bash” or “how to set up validation in spring boot”. We might “get there”, but it’ll take a whole lot of well written projects first, written by real humans, maybe with the help of AI here and there. Unless, that is, we build it with the ability to somehow learn and understand faster than humans.





  • jcg@halubilo.socialtoMemes@lemmy.ml"They" are on it 24/7
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    22 days ago

    I don’t mind a whoops somebody fucked right up error message if you let me click a button for more details. Or at the very least, give me a reference number I can tell somebody about. Some “software companies” don’t even properly log things on their end so nobody can solve shit.














  • The difference being consistency, imo. You look at high level CS players and their game sense will be occasionally so good that they’ll look like they’re aiming at people through walls. A cheater would probably track them through walls. A high level CS player would have a certain synergy between their aim, movement, and game sense - it all seems fairly consistent as far as skill level. A cheater will have really obvious gaps like God-tier aim with shitty movement, or something dumb like moving while also perfectly tracking heads, or just straight up making bad calls on where the enemies are because wallhacks typically don’t tell you when an enemy is behind.