311–320 of 437 posts
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Right, but it doesn't. It stops once you stop forcing it to do stuff.
I still don't understand your point, sorry. If it's a semantic nitpick about the meaning of "autonomous", I'm not interested - I've made my definition quite clear, and it has nothing to do with when agents stop doing things or what happens when they get turned off.
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Maybe, but that's not the case here so it is lost on me why you bring it up.
You're making claims about those systems not being autonomous. When we want to, we create them to be autonomous. It's got nothing to do with agency or survival instincts. Experiments like that have been done for years now - for example https://techcrunch.com/2023/04/10/researchers-populated-a-ti...
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I still don't understand your point, sorry. If it's a semantic nitpick about the meaning of "autonomous", I'm not interested - I've made my definition quite clear, and it has nothing to do with when agents stop doing things or what happens when they get turned off.
I think you should start caring about the meaning of words.
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You're making claims about those systems not being autonomous. When we want to, we create them to be autonomous. It's got nothing to do with agency or survival instincts. Experiments like that have been done for years now - for example https://techcrunch.com/2023/04/10/researchers-populated-a-ti...
Yes, because they aren't. Against your fantasy that some might be brought into existence sometime in the future I present my own fantasy that there won't be.
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Ok - where do AIs put the information that they "seek" from the internet?
I suspect there's a harsher argument to be made regarding "autonomous". Pull the power cord and see if it does what a mammal would do, or if it rather resembles a chaotic water wheel.
Pulling the power cord on a mammal means shutting off its metabolism. That predictably kills us.
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> Much like living things, they are recycling entropy and information to/from their environment (the internet) at runtime. 3 Problems with that assumption: a) Unlike living things, that information doesn't allow them to change. When a human touches a hotplate for the first time, it will (in addition to probably yelling and cursing a lot), learn that hotplates are dangerous and change its internal state to reflect tha…
> Unlike living things, that information doesn't allow them to change. The paper is talking about whole systems for AGI not the current isolated idea of pure LLM. Systems can store memories without issues. I'm using that for my planning system and the memories and graph triplets get filled out automatically, the get incorporated in future operations. > It can produce some sequence that may or may not cause some exter…
The situation is different in our brains, and we don't need to know how exactly human thinking works to acknowledge that...we know humans can infer meaning from language other than the statistical relationship between words.
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> this cannot be reached algorithmically > humans can (somehow) do this Is this not contradictory? Alternatively, in order to not be contradictory doesn't it require the assumption that humans are not "algorithmic"? But does that not then presuppose (as the above commenter brought up) that we are not a biochemical machine? Is a machine not inherently algorithmic in nature? Or at minimum presupposes that humans are mo…
> Alternatively, in order to not be contradictory doesn't it require the assumption that humans are not "algorithmic"? But does that not then presuppose (as the above commenter brought up) that we are not a biochemical machine? Is a machine not inherently algorithmic in nature? No, computation is algorithmic, real machines are not necessarily (of course, AGI still can't be ruled out even if algorithmic intelligence i…
Author seems to assume the latter condition is definitive, i.e. that real machines are not, and then derive extrapolations from that unproven assumption.
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> It absolutely does. Go run an agentic workflow using RAG on a local model. Do an md5 checksum of the model before and after usage. The result will be the same. > I agree that somewhere down the line there is a fixed set of tensors but that is not the algorithm. And for our current tools, that is fine. They are not the algorithm, the LLM is just a part of a large machine that involves countless other things. And tha…
Okay, yeah, like I said - not personally interested in debating the meaning of "AGI" or "understand". More power to you for thinking about it. > And that observable behavior includes hallucinations, a tendency to be repettive, falling for leading questions [...] I agree with you, obviously, these are common behaviours. You can improve the outcomes a lot with tight feedback loops for development workflows (like fast-r…
And that is, in a nutshell, my point. An AGI has to be autonomous. It cannot "go nuts" without handholding, same as a human needs to be able to (under normal operating conditions) remain coherent, even if left to their own devices.
> the environment deserves just as much thought in any analysis of an AI-based system.
Couldn't agree more, and since I know how much work these environments are to build, the people doing so well, have at least as much of my respect as the ones who devise the models.
But again, and I'm sorry I am pulling the "definition and meaning" card again: We cannot devise a system that requires a tight corset of an execution environment keeping tabs on it all the time lest it goes bananas, and still call it an AGI. Humans don't work that way, and no matter how we define "AGI", in the end I think we can agree that "something like how we do thinking" is pretty close to any valid definition, no?
If I need to lock something in 10 days to sunday to prevent it from going off the rails, I cannot really call it an AGI.
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Function != Computable Function / general recursive function. That's my point - computable functions are a [vanishingly] small subset of all functions. For example (and close to our hearts!), the Halting Problem. There is a function from valid programs to halt/not-halt. This is clearly a function, as it has a well defined domain and co-domain, and produces the same output for the same input. However it is not computa…
Non-computable functions are not relevant to this discussion, though, because humans can't compute them either, and so inherently an AGI need not be able to compute them. The point remains that we know of no function that is computable to humans that is not in the Turing computable / general recursive function / lambda calculus set, and absent any indication that any such function is even possible, much less an examp…
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> Unlike living things, that information doesn't allow them to change. The paper is talking about whole systems for AGI not the current isolated idea of pure LLM. Systems can store memories without issues. I'm using that for my planning system and the memories and graph triplets get filled out automatically, the get incorporated in future operations. > It can produce some sequence that may or may not cause some exter…
> That whole point implies that the situation is different in our brains. The situation is different in our brains, and we don't need to know how exactly human thinking works to acknowledge that...we know humans can infer meaning from language other than the statistical relationship between words.
Until you know how thinking works in humans, you can't say something else is different. We've got the same inputs available that we can provide to AI models. Saying we don't form our thinking based on statistics on those inputs and the state of the brain is a massive claim on its own.