- cross-posted to:
- [email protected]
- chatgpt
- [email protected]
- cross-posted to:
- [email protected]
- chatgpt
- [email protected]
I’ve been saying this for about a year since seeing the Othello GPT research, but it’s nice to see more minds changing as the research builds up.
Edit: Because people aren’t actually reading and just commenting based on the headline, a relevant part of the article:
New research may have intimations of an answer. A theory developed by Sanjeev Arora of Princeton University and Anirudh Goyal, a research scientist at Google DeepMind, suggests that the largest of today’s LLMs are not stochastic parrots. The authors argue that as these models get bigger and are trained on more data, they improve on individual language-related abilities and also develop new ones by combining skills in a manner that hints at understanding — combinations that were unlikely to exist in the training data.
This theoretical approach, which provides a mathematically provable argument for how and why an LLM can develop so many abilities, has convinced experts like Hinton, and others. And when Arora and his team tested some of its predictions, they found that these models behaved almost exactly as expected. From all accounts, they’ve made a strong case that the largest LLMs are not just parroting what they’ve seen before.
“[They] cannot be just mimicking what has been seen in the training data,” said Sébastien Bubeck, a mathematician and computer scientist at Microsoft Research who was not part of the work. “That’s the basic insight.”
Is there a difference between being a “stochastic parrot” and understanding text? No matter what you call it, an LLM will always produces the same output with the same input if it is at the same state.
An LLM will never say “I don’t know” unless it’s been trained to say “I don’t know”, it doesn’t have the concept of understanding. And so I lean on calling it a “stochastic parrot”. Although I think there is some interesting philosophic exercises, you could do on whether humans are much different and if understanding is just an illusion.
How do you know a human wouldn’t do the same? We lack the ability to perform the experiment.
Also a very human behaviour, in my experience.
I agree with you, I think its an interesting philosophical debate on whether we truly have free will, if we really have a level of understanding beyond LLMs do or if we are just a greatly more complex, biological version of an LLM. Like you said, we lack the ability to perform the experiment so I have to assume that our reactions are novel and spontaneous.
Fun thought experiment:
Let’s say we have a time machine and we can go back in time to a specific moment to observe how someone reacts to something.
If that person reacts the same way every time, does that mean that by knowing what they would do, you have removed their free will?
If you could travel back in time and observe a person over and over again react the same way is it different from observing a video tape?
Does traveling back in time guarantee that someone would react the same way in the same situation even?
I would think that it’s different, only because you have the potential to alter what could happen.
Maybe, maybe not, we’re entering the realm of Schrödinger’s cat as well as how time travel would actually work. Do we create some new branched timeline in travelling back? Do we enter an alternate universe entirely? Do we have a time machine where paradoxes are a problem? And the list can go on.
Because the human has “circuits” for coherrent thought and language was added later.
You might want to look up the definition of ‘stochastic.’
They’re not wrong. Randomness in computing is what we call “pseudo-random” in that it is deterministic provided that you start from same state or “seed”.
That is the quote from the article, not my words. Stochastic parrot is an oxymoron.
What’s a quote from the article? The term stochastic parrot? It opens on saying that might be an inaccurate description.