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Sparks of Artificial General Intelligence: Early Experiments with GPT-4

arxiv.org

41–50 of 244 posts

Re: Sparks of Artificial General Intelligence: Early Experiments with GPT-4

#41
post #10

I remember reading this somewhere - "There is a considerable overlap between the intelligence of the smartest bears and the dumbest tourists.". Though I do not think GPT-4 is even close to AGI it can definitely claim to be better at faking it than many intelligent beings can.

I heard that quote in the context of the difficulty of designing bear-resistant trash bins.

Watching adults struggle when encountering baby gates and other child proofing mechanisms for the first time is similarly amusing.

The difference between real intelligence and current attempts at artificial intelligence thus seem to be fundamentally the mode of learning, and thus understanding, rather than the raw knowledge and inference capability.

Or not. Nobody knows I'm actually a dog on the internet, after all.

Re: Sparks of Artificial General Intelligence: Early Experiments with GPT-4

#42

Earlier quoted context omitted.

That is pretty much the case, but I'm always taken back by how many people believe intelligence = directly replicating human thought. I thought the common consensus was instead that (artificial) intelligence was instead about mimicking enough of the process to provide the outcome. Largely because it's impossible to replicate something when we don't entirely know how it works. Major discoveries of basic aspects of the…

> Largely because it's impossible to replicate something when we don't entirely know how it works. On the contrary. These are mostly orthogonal.

How do you believe they're orthogonal?

Re: Sparks of Artificial General Intelligence: Early Experiments with GPT-4

#43
post #22

Earlier quoted context omitted.

Our of curiosity, what is GPT-4 getting wrong so often? It’s prettily wild to my own , admittedly easily impressed, mind.

Any variant of a "surprising" logic puzzle forces it to latch onto the surprising answer. Like whether two pounds of iron weighs more than one pound of feathers. Or any objects. It "expects" the twist, and always answers accordingly. It does so even if you change up the objects to be less tricky. > Which is heavier, a pound of marbles or two pounds of corn? Both weigh the same amount, which is a total of two pounds.…

I am terrible sorry, but I fail to see the logic in your 2+1=1+2 explanation of that answer. Would you be kind, and ELI5 it, if possible?

Re: Sparks of Artificial General Intelligence: Early Experiments with GPT-4

#44

> Given the breadth and depth of GPT-4’s capabilities, we believe that it could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence (AGI) system. I don't know why, but my brain refuses to accept GPT-4 as something close to AGI. Maybe I am wrong. It is hard to believe that our brain is just a bunch of attention layers and neural nets.

Do you think anything digital could ever become conscious?

The question is whether consciousness is computable. Can a Turing machine be conscious? Probably not.

https://www.newscientist.com/article/mg25634130-100-roger-pe...

https://www.youtube.com/watch?v=hXgqik6HXc0

Re: Sparks of Artificial General Intelligence: Early Experiments with GPT-4

#46

Earlier quoted context omitted.

> Largely because it's impossible to replicate something when we don't entirely know how it works. On the contrary. These are mostly orthogonal.

How do you believe they're orthogonal?

Biological reproduction for one. Copy/paste for another. Biological reproduction is only tenuously related to understanding and copy/paste isn’t even related at all. We can copy around weights and biases all day without understanding them.

Re: Sparks of Artificial General Intelligence: Early Experiments with GPT-4

#47
post #14

ChatGPT and its relatives are very very impressive on first impressions, but I've been using ChatGPT-3 and now 4 heavily every day since they became available to individuals and once you start using them this much it becomes very clear how NOT intelligent they are. It really just seems like extremely impressive statistical inference after this much use and finding so many failure modes. But it is still impressive how…

LLMs without any online storage can be at best convincing liars. Combining them together with an actual retrieval/QA system (e.g. by first fetching exact answer via a QA model and then reformulating output via GPT) could start feeling pretty real quickly.

Re: Sparks of Artificial General Intelligence: Early Experiments with GPT-4

#48

> Given the breadth and depth of GPT-4’s capabilities, we believe that it could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence (AGI) system. I don't know why, but my brain refuses to accept GPT-4 as something close to AGI. Maybe I am wrong. It is hard to believe that our brain is just a bunch of attention layers and neural nets.

Do you think anything digital could ever become conscious?

Based on the wording of your question, I can't see a way today to prove it never could, therefore the answer currently must be "Yes, it may someday be possible."

Note: This assumes that "conscious" as defined in this context is specific enough for the question to ever be meaningfully answered "Yes." This is a non-trivial assumption because there are criteria by which some would judge AIs as already conscious. Alternatively, some philosophers of mind have criteria by which they assert humans aren't conscious.

Re: Sparks of Artificial General Intelligence: Early Experiments with GPT-4

#49

> Given the breadth and depth of GPT-4’s capabilities, we believe that it could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence (AGI) system. I don't know why, but my brain refuses to accept GPT-4 as something close to AGI. Maybe I am wrong. It is hard to believe that our brain is just a bunch of attention layers and neural nets.

It's a well-established principle in computer science that the input/output behavior of a system may not capture all of its important properties. Take zero-knowledge proofs for example. Their entire point is that they are indistinguishable from randomly generated garbage from a specific distribution. The proofs only gain value if you make causal assumptions about the system that generated them.

I don't think systems like GPT-4 can ever be truly intelligent, because they simply output randomly generated garbage from a specific distribution. Their output may eventually be indistinguishable from that of a truly intelligent system, but the causal mechanism behind them is not intelligent.

On the other hand, most people lose their ability to think when they are under sufficient pressure (such as fighting for their lives). It's plausible that people are fundamentally no different from systems like GPT-4 in such situations. Then a language model could be a key part of an AGI, but true intelligence would also need higher-level causal mechanisms.

Re: Sparks of Artificial General Intelligence: Early Experiments with GPT-4

#50

Earlier quoted context omitted.

> It is hard to believe that our brain is just a bunch of attention layers and neural nets. Our brain isn't, but I'd wager the architectural complexity of a physical, neuronal brain is not optimized for all useful mental tasks, and has perhaps a fair amount of local maxima that are near vestigial in overall positive impact on cognition. Just because the human brain model of cognition is the only way nature has been a…

I agree that GI can have a different implementation compared to our human brain, but one thing is for sure: as of right now, the human brain can become more creative with a fraction of the data consumed by GPT-4. GPT-4 could be AGI, but it feels like cheating to achieve AGI by feeding the entire internet. If someone can build AGI with only the data that humans consume in their lifetime, then that, imho, is the real A…

Not sure I would call constant real-time perceptual stimuli since before birth "a fraction of the training data."
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