An LLM doesn’t think. It takes input and runs it through statistical layers until it returns output. It doesn’t learn either: the input does not change the model. Models are tuned, tweaked and generally curated to get the best experience. All experiments with letting a model be exposed to the public and “learn” directly have gone horribly wrong.
That’s what thinking is, you’re a model that takes sensory input and converts it into muscle movement. You do realize you too are a neural network… neurons are literally what we’ve based this technology on.
The input not changing the model is irrelevant, and I never claimed that, I claimed that they aren’t stochastic parrots.
Alpha go isn’t an LLM: It’s a reinforcement learning model combined with a Monte Carlo search. It uses deep learning and is fundamentally a different method of machine learning.
Yes, it’s something EVEN more primitive than an LLM, is my point, and yet it still does novel things. This even more primitive than LLM AI is already NOT a stochastic parrot, why would language models be one?
LLMs are definitely dangerous: the danger is that people believe them too much. It’s that CEOs believe they can replace their writers, it’s that the general public can generate bullshit faster than ever. They have irradiated the online sphere just like the nukes of the 40s irradiated all steel.
…duh?
I don’t think you responded to my post in any meaningful way.
This is not something you would see a stochastic parrot do, and I can point to many other articles displaying emergent properties not contained in their datasets. If it does things that are outside of its dataset, it’s not a stochastic parrot.
I read about this shit constantly, the notion that they’re stochastic parrots is reductionist nonsense.
You sound like you’re so used to people saying stupid shit about how it’s conscious that you expected me to believe that, and then argued with that belief. I don’t think they’re conscious, sentient, whatever, I think they’re not stochastic parrots and they have novel behaviors that aren’t necessarily in their datasets, or rather, can be inferred from parts of their datasets in order to make new things.