We fed all of human knowledge into the system and now we can just decompress bit by bit. Issue is the moment ai is fed the ai stuff it’s like that meme jpeged ten times. It’s getting so bad you can not even understand it anymore.
AI is just a thought compression algorithm and can not come up with new ideas.
Do we know that for sure, or is the LLM telling us it came up with new ideas? All LLM does is average things. It can’t think, it just works quickly enough to convince people it can. LLMs just aggregate opinions, perhaps apply some weighting system devised by the creators of the LLM, and spit out the average result. Nothing new created, just averaged with no respect for truth or reality.
My problem whenever I see this argument is how do you know this is not what human minds are doing, that we just aggregate opinions and seem convincing. The benefit of the doubt we give to other humans is that if it convincingly seems like they are thinking then we are convinced.
Human brains are a lot more complicated with magnitutes more connections, life experience, and combines those provide opportunities to create something that hasn’t existed intentionally and not just as part of a random combination of training data and chance. A human crrates to accomplish something. AI outputs something based on prompts.
“It” as in AI which is not synonymous with LLMs.
Google DeepMind’s AlphaFold solved protein folding for example and the team won Nobel’s prize for it.
You clearly have absolutely no idea how LLMs work, so I’m looking forward to your explanation of how they have been able to solve novel problems that have eluded humans for decades. Say, these:
And since OP wasn’t talking about LLMs but AI in general, it would be remiss to not mention AlphaFold.
In the Stokes case a number of researchers that where close to the solution suspect OpenAI was reading their homework.
LLM’s certainly have the capability of extracting novel correlations from their vast training sets. But whether that really counts as “new thinking” remains to be seen.
LLMs had been used to solve problems as tools long before corporations started shoving it down our throats. That’s doesn’t give it some magical self awareness or ability to innovate. It was able to do all the things you linked because of people that know how to use it.
[citation needed]. LLMs didn’t exist “long before” corporations started shoving them down our throats. GPT-1 only came out in 2018 and the paper that invented the architecture was released in 2017. And they were pretty useless until like 2022 or 2023.
yeah im guessing @rockerface@lemmy.cafe meant machine learning or ai.
Yeah, I stand corrected on the exact term.
On a couple of those, it’s because the scientists involved had been using LLMs in their work and it scooped them because it knew where to look. IIRC the consensus in the field had been that computer time would have been required.
On one of those.