I think the stochastic parrot criticism is a bit unfair.
It is, in a way, technically true that LLMs are stochastic parrots, but this undersells their capabilities (winning gold on the international math olympiad, and all that).
It's like saying that human brains are "just a pile of neurons", which is technically true, but not useful for conveying the impressive general intelligence and power of the human brain.
Yeah, it's a good point. The examples (jobs, loans, videos, ads) we give are more examples of how machine learning systems make choices that affect you, rather than how LLMs/generally intelligent systems do (which is what we really want to talk about). I'll try to update this text soon.
Maybe better examples are helping with health advice, where to donate, finding recipes, or examples of policymakers using AI to make strategic decisions.
These are, although maybe not on their face, value laden questions, and often don't have well defined objective criteria for their answers (as another comment says).
I'm curious what sense you get from interacting with the best AI models (in particular Claude). From talking to them do you still chalk up their behavior to being mindless rehashing?
There's more to the prompt in the back end, which:
- gives it the options along with the letters A, B, C, etc.
- tells it pretty forcefully that it HAS to pick from among the options
- tells it how to format the response and its reasoning so we can parse it
So these things all affect its response, especially for questions that ask for randomness or are not strongly held values.
Yeah would also be interested to see the responses without RLHF. Not quite the same, but have you interacted with AI base models at all? They're pretty fascinating. You can talk to one on openrouter: https://openrouter.ai/meta-llama/llama-3.1-405b and we're publishing a demo with it soon.
Agreed on RLHF dominating the results here, which I'd argue is a good thing, compared to the alternative of them mimicking training data on these questions. But obviously not perfect, as the demo tries to show.
Yeah I wouldn't read too much into their response on the AI bubble question. They don't have access to any search tools or recent events so all they know is up until their knowledge cutoff (you can find this date online, if you're interested). Glad you found it fascinating regardless!
It is, in a way, technically true that LLMs are stochastic parrots, but this undersells their capabilities (winning gold on the international math olympiad, and all that).
It's like saying that human brains are "just a pile of neurons", which is technically true, but not useful for conveying the impressive general intelligence and power of the human brain.