I am a software engineer by trade, so biases’ being what they are. But what I was more trying to demonstrate is that it is provable. Not that making the proof is easy.
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- G_M0N3Y_2503@lemmy.ziptoTechnology@lemmy.world•Linus Torvalds used AI to fix a Linux bug, and now LLM critics on Linux face an uncomfortable choiceEnglish1·4 days ago
- G_M0N3Y_2503@lemmy.ziptoTechnology@lemmy.world•Linus Torvalds used AI to fix a Linux bug, and now LLM critics on Linux face an uncomfortable choiceEnglish1·5 days ago
hmmm, I just copied from Wikipedia as my primary source. That was the faux pas that was cool before AI.
- G_M0N3Y_2503@lemmy.ziptoTechnology@lemmy.world•Linus Torvalds used AI to fix a Linux bug, and now LLM critics on Linux face an uncomfortable choiceEnglish3·5 days ago
I know you said all, but I’m curious which part do you think is horse shit? Do you think Torvalds is lying about using AI all together? or just how useful AI actually was? The commit with the alleged AI use is in the an RC for the next release, and it is authored by Torvalds.
- G_M0N3Y_2503@lemmy.ziptoTechnology@lemmy.world•Linus Torvalds used AI to fix a Linux bug, and now LLM critics on Linux face an uncomfortable choiceEnglish1·5 days ago
Code is probably one of the easiest things to verify, for that reason I struggle to see any other viable uses for LLMs tbh.
user: write code that correctly asserts what 1+1 equals. LLM: assert_eq!(1 + 1, 4); LLM: hmmm, that crashed. LLM: assert_eq!(1 + 1, 3); LLM: hmmm, that also crashed, I must be doing something wrong, let me try one more time. LLM: assert_eq!(1 + 1, 2); LLM: that worked! LLM Response: assert_eq!(1 + 1, 2);user: what does this sentence mean? "Buffalo buffalo Buffalo buffalo buffalo buffalo Buffalo buffalo" LLM Response: This doesn't mean anything, or someone really likes buffalo'sI can always run the code to check, I still don’t know how that sentence makes sense.
- G_M0N3Y_2503@lemmy.ziptoTechnology@lemmy.world•Why Normal People Aren’t Using AI AgentsEnglish2·29 days ago
The edge case is software development, for the bog standard stuff I write at work it probably helps me get work done about 15%-30% faster and with costs of $200-$400 USD a month the math actually works out. At current prices anyway. Also the electricity costs of running open weight models is even cheaper and if there is a pop HW prices may make that an obvious choice too. The worst case IMO would be a slow boil of prices to recoup the unsustainable growth then a slow decline to wherever normal ends up. In that case everyone is left indignant.
- G_M0N3Y_2503@lemmy.ziptoTechnology@lemmy.world•DeepSeek's Liang Wenfeng Breaks His Silence: In a rare four-hour talk, the reclusive founder reveals an almost Daoist philosophy of AI—AGI as a tide no company can own...English2·1 month ago
Agreed, However I also wonder how or if LLMs could help with what we don’t know we need. With the processing pace of LLMs and the massive context the can processes at once. It seems like it could make the broader connections that are usually the harder to find more accessible.
Ah, that’s probably it. And yeah, governments need to figure out how to manage this. I think it’s destined to be bound by whatever is actually economical post hype. Not pending efficiency breakthroughs of the likes of mores law.