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Is anyone else scared of how fast AI is advancing?
(lemmy.world)
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Anytime I ask it about things I'm knowledgeable about, it falls on it's face. It only seems smart on topics I don't know shit about (this red flag has spotlights on it!). Given this, I cannot trust it on anything lest I be led down false paths. Given how LLMs work, I don't see this problem as fixable.
I have found them useful for search term generation. (Using a topic I know things about) If I need a more powerful drill for screwing lag bolts into hardwood and I'm not finding what I need, asking it and and getting back the keyword 'impact driver' is helpful, as it lets me go search for what that is and if it is the solution to my need for a more powerful drill. Note: I do not let it teach me about impact drivers (as it falls on it's face all the fucking time), only use it to get the keyword to then use to search the internet.
To circle back to your question, I'm not scared with how fast they are advancing. I'm scared by how many people think they are good at everything and put them in places they don't belong.
How long ago did you try?! Have an example?
LLMs now search the web and compile results and info very fast. They do exactly what I’ve been doing for decades, searching and skimming results.
If you ask one “I need a more powerful drill for screwing lag bolts into hardwood” it’ll toss you a whole write up on things.
I expected it to get this one wrong and it did; I expected that as Hollywood portrays this wrong and people don't have an intuitive understanding of missile rocketry. Interceptor missiles only burn for a few seconds, get going very fast, then coast to their target. It is just flat wrong here.
I then fixed my grammar mistake and asked again, and poof, 100% opposite answer. I literally got the OPPOSITE ANSWER just because I fixed a grammar mistake. This fundamentally cannot be trusted for actual learning.
I see. It definitely gets thrown off by the perceived confidence in the question, which is made to steer it toward a wrong response. It’s training data likely has far less instances of text that derails the question based on incorrect original assumptions.
Thanks for the response!