this post was submitted on 09 Jan 2025
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I've read it is still well valued because people will keep asking questions there when LLM can't answer, so they remain a precious source of post LLM curated Q&A.
That might be true if any human could reasonably ask a question there now. Ask a question, and you are likely going to see it removed for a variety of reasons.
To be honest, I had a bad experience a few years ago when I wanted to try contributing, and I never tried again. Yet, I think it's really hard to strike a balance of freedom and constrains for organically curated Q&A, so I try not to be too fast on judging them considering the service that they indubitably provided to millions of people.
...for now.
Until it's just AIs answering questions asked by other AIs while human admins block human accounts..
Solaria, here we come.
Yeah, AI has become good enough at this point that you can provide it with a large blob of context material - such as API documentation, source code, etc. - and then have it come up with its own questions and answers about it to create a corpus of "synthetic data" to train on. And you can fine-tune the synthetic data to fit the format and style that you want, such as telling it not to be snarky or passive-aggressive or whatever.
It can reproduce an api. Can't solve actual problems. LLMs are completely incapable of innovation.
That's not really true though.. They come up with brand new sentences all the time.
It can but you to closely midwife it into doing so.
And yet the synthetic training data works, and models trained on it continue scoring higher on the benchmarks than ones trained on raw Internet data. Claim what you want about it, the results speak louder.
This is the peak, though. They require new data to get better but most of the available new data is adulterated with AI slop. Once they start eating themselves it's over.
You are speaking of "model collapse", I take it? That doesn't happen in the real world with properly generated and curated synthetic data. Model collapse has only been demonstrated in highly artificial circumstances where many generations of model were "bred" exclusively on the outputs of previous generations, without the sort of curation and blend of additional new data that real-world models are trained with.
There is no sign that we are at "the peak" of AI development yet.
We're already seeing signs of incestuous data input causing damage. The more that AI takes over, the less capable it will be.
Are we, though? Newer models almost universally perform better than older ones, adjusted for scale. What signs are you seeing?
The results aren't worth the expense. So-called "AI" is the biggest bubble since the great recession.
Nah, I'm still giving that one to the blockchain. LLMs are going to be useful for a while, but Ethereum still hasn't figured out a real use, and they're the only ones that haven't given up and moved fully into coin gambling.
Blockchain currencies aren't a bubble, they're a scam.