161–170 of 393 posts
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Given many people don’t have an inner monologue and function just fine, it’s more likely inner monologue is a product of the reasoning process and not it’s mechanism.
I think you’re using “inner monologue” too literally. It could be a progression of pictures, emotions, etc.
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If you really think about what an LLM is you would think there is no way that leads to general purpose AI. At the same time though they are already doing way more than we thought they could. Maybe people were surprised by what OpenAI achieved so now they are all just praying that with enough compute and the right model AGI will emerge.
LLMs are the language center of an AI. They in no way purport to be: long term memory, critical thinking engines, calculators. If we want those things we can build them. Building them into the language center would be absurd and weird.
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> If you really think about what an LLM is you would think there is no way that leads to general purpose AI It is an autoregressive sequence predictor/generator. Explain to me how humans are fundamentally different
AI needs to see thousands or millions of images of a cat before they reliably can identify one. The fact that a child needs to only see one example of a cat to know what a cat is from then on seems to point to humans having something very different.
Not if they inherit from a previous generation of AI. But even if they did, a different training speed does not imply a different capability
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It’s commonly conjectured that the emergence of human-level reasoning wouldn’t have been possible without the development of language. Personally, I’m able to suppress “word thoughts” in my head (for a short time), but then I lose almost all of my reasoning ability. I could imagine that reasoning is language-based even when it’s not conscious for some people. An internal process being there, and being conscious of it…
Maybe, but symbolic thought can get pretty far away from what we generally call "language." I bet you can reason 1+3x=22 pretty easily without any words whatsoever, or the sound of one ascending octave after another, or the approximate G-force induced on your body if you take the next turn without applying the brakes. All of these forms of reasoning are true and useful calculations: when we talk about "intuition" wha…
Regarding your edit, no, I think the key aspect of the kind of reasoning we are missing in current AI is the ability to hold the reasoning in your mind, and to iterate on it and evaluate it (judge it) within your mind.
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"Prove me wrong?" That's not how this works. Your implicit claim here is that human cognition and LLM functioning are fundamentally similar. That claim requires substantiation.
I actually did a full write-up on this here fyi: https://photonlines.substack.com/p/intuitive-and-visual-guid... . You can skip most of this and scroll down to the end-section called 'The Mental Model for Understanding LLMs' where I try to map how transformers are able to mimic human thinking. I think that comparing them to auto-associative / auto-regressive networks is actually a really good analogy FYI and I do bel…
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In this particular case, is there any reason why we simply can't take their word for it? This is not a case of where if I say "weak" or "strong", most people pick strong because no one wants to be weak, even if the context is unknown (nuclear force for example).
> is there any reason why we simply can't take their word for it? because if we give them a problem to solve in their head and just give us the answer, they will. By problem I mean planning a trip, a meal, how to pay the mortgage, etc. It's impossible to plan without an internal monologue. Even if some people claim theirs is 'in images'.
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I honestly thought about this recently when I was trying to see the limits of Claude Opus. Some of the problems I gave it, what if instead of telling it to solve the problem I asked it to write the script and then give me the command and inputs needed to properly run it to get the answer I needed. That way instead of relying on the LLM to do properly analysis of the numbers it just needs to understand enough to write…
I'm not sure what you mean by 'it will not scale well.' When we humans learn that we make a mistake - we make a note and we hold the correct answer in memory - the next time we're prompted with a similar prompt, we can use our old memories to come up with the correct solution. I just did a simple test for this same exact problem using ChatGPT 3.5: 'Can you reformulate the following problem using Prolog? When you exec…
I'm using the default free model in the app, based on GPT4.
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I don't think anybody who actually uses LLMs thinks they are general purpose AI. Like you ask it to do one thing it's amazing, but then you try to modify or do something with extra steps, or just anything with any complexity to it and it falls over.
> I don't think anybody who actually uses LLMs thinks they are general purpose AI. I would like to believe that but I have had too many conversations with people who basically think it already is. Including in one situation of a fellow engineer. It feels like more and more "we" are in a bubble of actually having some knowledge of how this works, what the actual limitations are, and what it just is not. While there is…