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> ChatGPT is a glorified word predictor. It isn’t sentient. It doesn’t know what it’s saying, and yes, you can coax it into admitting that it wants to take over the world or saying hurtful things (although it was specially conditioned during training to try to suppress such output). It’s simply stringing words together using an expansive statistical model built from billions of sentences. How do you differentiate it…
Earlier quoted context omitted.
Can you explain your proof of that?
Not OP, but basically: Humans have the capacity to come up with new language, new ideas, and basically everything in our human world was made up by someone. ChatPT or similar, without any training data, cannot do this. Thus they're simply imitating
Art generators are the most obvious example to me. They regularly create depictions of entirely new animals that may look like a combination of known species.
People got a kick out of art AIs struggling to include words as we recognize them. How can we say what looked like gibberish to us wasn't actually part of a language the AI invented as part of the art piece, like Tolkien inventing elvish for a book?
Earlier quoted context omitted.
Without any external plugins, GPT can encode and decode base64 strings that are totally new. Again "luck" ? If a system is so lucky that it gives you the right answer 9 times out of 10, it's perhaps not luck anymore.
It cannot, encode base64 it only remember, see this conversation: https://news.ycombinator.com/item?id=34322223
In your message you say it is gibberish, but I have completely different results and get very good Base64 on super long and random strings.
I frequently use Base64 (both ways) to bypass filters in both GPT-3 and 4/Bing so I'm sure it works ;)
It sometimes make very small mistakes but overall amazing.
At this stage if it can work on random data that never appeared in the training set it's not just luck, it means it has acquired that skill and learnt how to generalise it.
Earlier quoted context omitted.
Can you explain your proof of that?
Not OP, but basically: Humans have the capacity to come up with new language, new ideas, and basically everything in our human world was made up by someone. ChatPT or similar, without any training data, cannot do this. Thus they're simply imitating
And what do you think of the Mark Twain quote:
“ There is no such thing as a new idea. It is impossible. We simply take a lot of old ideas and put them into a sort of mental kaleidoscope. We give them a turn and they make new and curious combinations. We keep on turning and making new combinations indefinitely; but they are the same old pieces of colored glass that have been in use through all the ages.”
I’d argue ChatGPT can indeed be creative, as it can combine ideas in new ways.
> ChatGPT is a glorified word predictor. It isn’t sentient. It doesn’t know what it’s saying, and yes, you can coax it into admitting that it wants to take over the world or saying hurtful things (although it was specially conditioned during training to try to suppress such output). It’s simply stringing words together using an expansive statistical model built from billions of sentences. How do you differentiate it…
When a silicon based hardware computes that as a response, it isn't because a whole bunch of chemical reactions is making it desire particular sensations and hormonal responses, but because the limited amount of information on human horniness conveyed as text strings implies it's a high probability continuation to its input (probably because someone forgot to censor the training set...)
Insisting comparable outputs make the two are fundamentally the same isn't so much taking the human mind off a pedestal as putting a subset of i/o that pleases the human mind on a pedestal and arguing nothing else in the world makes any material difference.
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> That would point to higher-level phenomena going on inside ChatGPT and its ilk, than merely statistics and predictions. No, it wouldn't, because nothing in "higher-level phenomena" precludes it being caused by statistics and predictions.
I don't understand that. In computer science everyone learned that computation is best described and explained at several levels of abstraction. E.g., HW/SW interface; machine code vs C++; RTL vs architecture, the list of levels of abstractions goes on and on. So what is the reason for not appropriately extending this idea to analyzing whatever a neural network is doing?
In general abstractions are not perfect, hence 'leaky abstractions'.
> ChatGPT is a glorified word predictor. It isn’t sentient. It doesn’t know what it’s saying, and yes, you can coax it into admitting that it wants to take over the world or saying hurtful things (although it was specially conditioned during training to try to suppress such output). It’s simply stringing words together using an expansive statistical model built from billions of sentences. How do you differentiate it…
Well for a start the human mind involves a series of chemical reactions optimised by evolutionary wiring and physical world interaction towards self replication, so when a human says "I feel horny" there's a whole bunch of stuff going on in there that there's no reason to suspect is replicated in a neural network optimised for text transformation. When a silicon based hardware computes that as a response, it isn't be…
Although at this point it feels like these are just engineering problems as opposed to deep philosophical questions. The capabilities of ChatGPT are emergent phenomena created from the extremely simple training task of next word prediction. IMO this is very strong evidence that the rest of our cognitive abilities can be replicated this way as well, all it takes is the right environment and training context. It might start with something like this: https://www.deepmind.com/blog/building-interactive-agents-in... that uses cross-attention with an LLM to predict its next actions.
Some speculative ideas I've had:
- Brains (in animals) have largely evolved to predict the future state of the environment, to evade predators, find food and so on.
- To be effective, this predictive model must take its own (future) actions into account, a requirement for counterfactual thinking.
- This means that the brain needs a predictive model of its own actions (which does not necessarily align with how the brain actually works)
- Consciousness is the feedback loop between our senses (our current estimated state) and this predictive model of our own actions.
- All of this is to better predict the future state of the environment, to aid in our survival. For a hypothetical AI agent, a simple prediction loss may well be enough to cause these structures to form spontaneously. Similarly a theory of mind is the simplest, "most compressed" way to predict the behavior of other agents in the same environment.
> ChatGPT is a glorified word predictor. It isn’t sentient. It doesn’t know what it’s saying, and yes, you can coax it into admitting that it wants to take over the world or saying hurtful things (although it was specially conditioned during training to try to suppress such output). It’s simply stringing words together using an expansive statistical model built from billions of sentences. How do you differentiate it…
Human mind can perform actual reasoning, while ChatGPT only mirrors the output of reasoning and when it gets output correctly it's due to mixture of luck and closeness to training material. Human mind or even something like Wolfram Alpha can perform reasoning.
Earlier quoted context omitted.
Can you explain your proof of that?
Not OP, but basically: Humans have the capacity to come up with new language, new ideas, and basically everything in our human world was made up by someone. ChatPT or similar, without any training data, cannot do this. Thus they're simply imitating