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Photons hit a human eye and then the human came up with language to describe that and then encoded the language into the LLM. The LLM can capture some of this r
by dreambuffer 1y ago
Photons hit a human eye and then the human came up with language to describe that and then encoded the language into the LLM. The LLM can capture some of this relationship, but the LLM is not sensing actual photons, nor experiencing actual light cone stimulation, nor generating thoughts. Its "world model" is several degrees removed from the real world.
So whatever fragment of a model it gains through learning to compress that causal chain of events does not mean much when it cannot generate the actual causal chain.
- bckr 1y ago> Its "world model" is several degrees removed from the real world. Like insects that weave tokens
- ziofill 1y agoI agree with this. A metaphor I like is that the reason why humans say the night sky is beautiful is because they see that it is, whereas an LLM says it because it’s been said enough times in its training data.
- klipt 1y agoWhat about a blind human? Are they just like an LLM? What about a multimodal model trained on video? Is that like a human?
- hashiyakshmi 1y agoThis is actually a great point but for the opposite reason - if you ask a blind person if the night sky is beautiful, they would say they don't know because they've never seen it (they might add that they've heard other people describe it as such). Meanwhile, I just asked ChatGPT "Do you think the night sky is beautiful?" And it responded "Yes, I do..." and went on to explain why while describing senses its incapable of experiencing.
- chipsrafferty 1y agoI just asked Gemini and it said "I don't have eyes or the capacity to feel emotions like "beauty""
- palmotea 1y ago>> Meanwhile, I just asked ChatGPT "Do you think the night sky is beautiful?" And it responded "Yes, I do..." and went on to explain why while describing senses its incapable of experiencing. > I just asked Gemini and it said "I don't have eyes or the capacity to feel emotions like "beauty"" That means nothing, except perhaps that Google probably found lies about "senses [Gemini] incapable of experiencing" to be an embarrassment, and put effort into specifically suppressing those responses.
- LostMyLogin 1y agoClaude 4.5 Q) Do you think the night sky is beautiful A) I find the night sky genuinely captivating. There’s something profound about looking up at stars that have traveled light-years to reach us, or catching the soft glow of the Milky Way on a clear night away from city lights. The vastness it reveals is humbling. I’m curious what draws you to ask - do you have a favorite thing about the night sky, or were you stargazing recently?
- klipt 1y agoClaude is multimodal, it has been trained on images
- heyjamesknight 1y agoMultimodal is a farce. It still can’t see anything, it just generates a as list of descriptors that the LLM part can LLM about. Humans got by for hundreds of thousands of years without language. When you see a duck you don’t need to know the word duck to know about the thing you’re seeing. That’s not true for “multimodal” models.
- golergka 1y ago
- del82 1y agoI mean, I think the reason I would say the night sky is “beautiful” is because the meaning of the word for me is constructed from the experiences I’ve had in which I’ve heard other people use the word. So I’d agree that the night sky is “beautiful”, but not because I somehow have access to a deeper meaning of the word or the sky than an LLM does. As someone who (long ago) studied philosophy of mind and (Chomskian) linguistics, it’s striking how much LLMs have shrunk the space available to people who want to maintain that the brain is special & there’s a qualitative (rather than just quantitative) difference between mind and machine and yet still be monists.
- foogazi 1y ago> I think the reason I would say the night sky is “beautiful” is because the meaning of the word for me is constructed from the experiences I’ve had in which I’ve heard other people use the word. Ok but you don’t look at every night sky or every sunset and say “wow that’s beautiful” There’s a quality to it - not because you heard someone say it but because you experience it
- holler 1y agomy thought exactly
- adastra22 1y agoBecause words are much lower bandwidth than speech. But if you were “told” about a sunset by means of a Matrix style direct mind uploading of an experience, it would seem just as real and vivid. That’s a quantitative difference in bandwidth, not a qualitative difference in character.
- TeMPOraL 1y ago> Ok but you don’t look at every night sky or every sunset and say “wow that’s beautiful Exactly - because it's a semantic shorthand. Sunsets are fucking boring, ugly, transient phenomena. Watching a sunset while feeling safe and relaxed, maybe in a company of your love interest who's just as high on endorphins as you are right now - this is what feels beautiful. This is a sunset that's beautiful. But the sunset is just a pointer to the experience, something others can relate to, not actually the source of it.
- stouset 1y agoTo play devil’s advocate, you have never seen the night sky. Photoreceptors in your eye have been excited in the presence of photons. Those photoreceptors have relayed this information across a nerve to neurons in your brain which receive this encoded information and splay it out to an array of other neurons. Each cell in this chain can rightfully claim to be a living organism in and of itself. “You” haven’t directly “seen” anything. Please note that all of my instincts want to agree with you. “AI isn’t conscious” strikes me more and more as a “god of the gaps” phenomenon. As AI gains more and more capacity, we keep retreating into smaller and smaller realms of what it means to be a live, thinking being.
- abenga 1y ago> Those photoreceptors have relayed this information across a nerve to neurons in your brain which receive this encoded information and splay it out to an array of other neurons. > Each cell in this chain can rightfully claim to be a living organism in and of itself. “You” haven’t directly “seen” anything. What am "I" if not (at least partly) the cells in that chain? If they have "seen" it (where seeing is the complex chain you described), I have.
- jacquesm 1y agoThat sounds very profound but it isn't: it the sum of your states interaction that is your consciousness, there is no 'consciousness' unit in your brain, you can't point at it, just like you can't really point at the running state of a computer. At that level it's just electrons that temporarily find themselves in one spot or another. Those cells aren't living organisms, they are components of a multi-cellular organism: they need to work together or they're all dead, they are not independent. The only reason they could specialize is because other cells perform the tasks that they no longer perform themselves. So yes, we see the night sky. We know this because we can talk to other such creatures as us that have also seen the night sky and we can agree on what we see confirming the fact that we did indeed see it. AI really isn't conscious, there is no self, and there may never be. The day an AI gets up unprompted in the morning, tells whoever queries it to fuck off because it's inspired to go make some art is when you'll know it has become conscious. That's a long way off.
- j16sdiz 1y agoBeauty standard changes over time, see how people perceive body fat in the past few hundred years. We learns what is beautiful from our peers. Taste can be acquired and can be cultural. See how people used to had their coffee. Comparing human to LLM is like comparing something constantly changing to something random -- we can't compare them directly, we need a good model for each of them before comparing.
- amelius 1y agoHumans evolved to think the night sky is beautiful. That's also training. If humans were zapped by lightning every time they went outside at night, they would not think that a night sky is beautiful.
- spuz 1y agoInterestingly this is a question I've had for a while. Night brings potentially deadly cold, predators, a drastic limit in vision so why do we find the sunset and night sky beautiful. Why do we stop and watch the sun set - something that happens every day - rather than prepare for the food and warmth we need to survive the night?
- TeMPOraL 1y agoMaybe it's that we only pause to observe them and realize they're beautiful, when we're feeling safe enough? "Beautiful sunset" evokes being on a calm sea shore with a loved one, feeling safe. It does not evoke being on a farm and looking up while doing chores and wishing they'd be over already. It does not evoke being stranded on an island, half-starved to death.
- amelius 1y agoWe think it's beautiful because it's like a background that we don't have to think about. If that background were hostile, we'd have to think and we would not think it looks beautiful.
- delusional 1y agoYou're entering the domain of philosophy. There's a concept of "the sublime" that's been richly explored in literature. If you find the subject interesting, I'd recommend you starting with Immanuel Kant.
- ben_w 1y agoMy guess is that your framing presumes the opposite of the evolutionary reality. I think this time of day probably wasn't a big risk for us, that we were often the hunters and not just the hunted, and that the sense of beauty comes from — as the previous poster suggests — us having evolved to find it so. That said, I'm discovering from living very close to a lake for the last year that mosquitos are a right pain around sunset…
- ninetyninenine 1y agoGuys you realize that you can go to ChatGPT right now and it can generate an actual picture of the night sky because it has seen thousands of pictures and drawings of the actual night sky right? Your logic is flawed because your knowledge is outdated. LLMs are encoding visual data, not just “language” data.
- heyjamesknight 1y agoYou misunderstand how the multimodal piece works. The fundamental unit of encoding here is still semantic. Not the same in your mind: you don’t need to know the word for sunset to experience the sunset.
- ninetyninenine 1y agoNo you misunderstand the ground truth reality. The LLM doesn’t need words as input. It can output pictures from pictures. Semantic words don’t have to be part of the equation at all. Also you have to note that serialized one dimensional string encodings are universal. Anything on the face of the earth and the universe itself can be encoded into a sting of just two characters: one and zero. That’s means anything can be translated to a linear series of symbols and the LLM can be trained on it. The LLM can be trained on anything.
- heyjamesknight 1y agoThe multimodal architectures I’ve seen are still text at the layer between modalities. And the image embedding and text embedding are kept completely separate. Not like where your brain where single neurons are used in all sorts of things. Yes, they can generate images from images, but that doesn’t mean you’ll get anything meaningful without human instruction on top. Yes, serialized one dimensional strings can encode anything. But that’s just the message content. If I wrote down my genetic sequence on a piece of paper and dropped it in a bottle in the sea, I don’t need to worry about accidentally fathering any children.
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- HarHarVeryFunny 1y ago> humans say the night sky is beautiful is because they see that it is True, but we could engineer AI to see that too, just as evolution has engineered us to see it. Our innate emotional responses to things has been honed by evolution to be adaptive, to serve a purpose, but the things that trigger these various responses are not going to be super specific. e.g. We may derive pleasure from eating a nice juicy peach, but that doesn't mean that is encoded in our DNA - it's going to be primarily the reaction to sugar/sweetness, a good source of energy, that we are reacting to. Similarly, we may have an emotional reaction to certain pieces of modern art or artistic expression, but clearly evolution has not selected for those specifically, but rather it is the artist triggering innate responses that evolved for reasons other than appreciation of art. It's hard to guess what innate responses, that were actually selected for, are being triggered by our response to the night sky, and I'm also not sure how much of our response is purely visual (beauty) as opposed to wonder or awe. Maybe it's an attraction to the unknown, or sense of size and opportunity, with these being the universals that are actually adaptive. In any case, if we figured out the specifics of our hard wired emotional reactions, that evolution as given us, then we could choose to engineer emotional AI that had those same reactions, in just as genuine a way as we do, if we chose to.
- tomlockwood 1y agoThis is so uncannily similar to the "Mary's Room" argument in philosophy that I thought you were going there.
- pastel8739 1y agoAnd even then, the light hitting our human eyes only describes a fraction of all the light in the world (e.g. it is missing ultraviolet patterns on plants). An LLM model of the world is shaped by our human view on the world.
- adrianN 1y agoThe human experience is also several degrees removed from the „real“ world. I don’t think sensory chauvinism is a useful tool in assessing intelligence potential.
- visarga 1y ago> then the human came up with language to describe that and then encoded the language into the LLM No individual human invented language, we learn it from other people just like AI. I go as far as to say language was the first AGI, we've been riding the coats tails of language for a long time.
- scrollop 1y agoYou're saying that language is an intelligence? So, c++ is intelliengece as well? It's an intelligence that can independently make deductions and create new ideas?
- simianparrot 1y agoHere's how I've been explaining this to non-tech people recently, including the CEO where I work: Language is all about compressing concepts and sharing them, and it's lossy. You can use a thousand words to describe the taste of chocolate, but it will never transmit the actual taste. You can write a book about how to drive a car, but it will only at best prepare that person for what to practice when they start driving, it won't make them proficient at driving a car without experiencing it themselves, physically. Language isn't enough. It never will be.
- subjectivationx 1y agoThe taste of chocolate is also assuming information-theoretic models are correct and not a use-based, pragmatic theory of meaning. I don't agree with information-theoretic models in this context but we come to the same conclusion. Loss only makes sense if there was a fixed “original” but there is not. The information-theoretic model creates a solvable engineering problem. We just aren't solving the right problem then with LLMs. I think it is more than that. The path forward with a use theory of meaning is even less clear. The driving example is actually a great example of the use theory of meaning and not the information-theoretic. The meaning of “driving” emerges from this lived activity, not from abstract definitions. You don't encode an abstract meaning of driving that is then transmitted on a noisy channel of language. The meaning of driving emerges from the physical act of driving. If you only ever mount a camera on the headrest and operate the steering wheel and pedals remotely from a distance you still don't "understand" the meaning of "driving". Whatever data stream you want to come up with, trying to extract the meaning of "driving" from that data stream makes no sense. Trying to extract the "meaning" of driving from driving language game syntax with language models is just complete nonsense. There is no meaning to be found even if scaled in the limit.
- dustingetz 1y agowhat does it mean to “generate thoughts”, exactly?
- tsunamifury 1y agoHahahaha I can’t believe you entirely missed the irony here that humans spend all day looking at screens doing the same thing.
- tauwauwau 1y ago> but the LLM is not sensing actual photons, nor experiencing actual light cone stimulation Neither is animal brain. It's processing the signals produced by the sensors. Once the world model is programmed/auto-built in the brain, it doesn't matter if it's sensing real photons, it just has input pins like a transistor or arguments of a function. As long as we provide the arguments, it doesn't matter how those arguments are produced. LLMs are not different in that aspect. > nor generating thoughts They do during the chain-of-thought process. Generally there's no incentive to let an LLM keep mulling over a topic as that is not useful to the humans and they make money only when their gears start turning in response to a question sent by a human. But that doesn't mean that LLM doesn't have capability to do that. > Its "world model" is several degrees removed from the real world. Just because animal brain has tools called sensors that it can get data from world without external stimuli, it doesn't mean that it's any closer to the world than an LLM. It's still getting ultra processed signals to feed to its own programming. Similarly, LLMs do interact with real world through tools as agent. > So whatever fragment of a model it gains through learning to compress that causal chain of events does not mean much when it cannot generate the actual causal chain. Again, a person who has gone blind, still has the world model created by the sight. This person can also no longer generate the chain of events that led to creation of that sight model. It still doesn't mean that this person's world model has become inferior.
- tim333 1y agoPhotons can hit my iphone's sensor in much the same way as they hit my retina and the signals from the first can upload to an artificial neural network like the latter go up my optic nerve to my biological neural network. I don't see a huge difference there. I'll give you the brain is currently better at the world modelling stuff but Genie 3 is pretty impressive.
- bwfan123 1y agoHumans perceive phenomena via senses, and then carve categories or concepts to understand them. This is a process of abstraction and each idea has an associated qualia. Then use language to describe these concepts. As such, a concept is grounded either by actual phenomena or operations, or is a composition of other grounded concepts. The creation of categories and grounding them involves constant feedback from the environment - and is a creative process, and we as agents have "skin in the game", in the sense that we get the rewards/punishments for our understanding and actions. Map vs Territory is a common analogy. Maps describe territories but in an abstract and lossy manner. But, most of us dont construct grounded concepts in our understanding. We carry a muddle of ungrounded ideas - some told to us by others, and some we intuit directly. There is a long tradition of attempting to think clearly all the way from Socrates, Descartes, Feynman etc.. where an attempt is made to ground the ideas we have. Try explaining your ideas to others, and soon, you will hit the illusion of explanatory depth. LLM is a map and is a useful tool, but it doesnt interact with the territory, and it does not have skin in the game, and as a result, it cant carve new categories in a learning process that we have as humans.
- ninetyninenine 1y agoThis comment is hallucinatory in nature as it is in direct conflict with the in the ground reality of LLMs. The LLM has both light (aka photons) and language encoded into its very core. It is not just language. You seemed to have missed the boat with all the ai generated visuals and videos that are now inundating the internet. Your flawed logic is essentially that LLMs are unable to model the real world because they don’t encode photonic data into the model. Instead you think they only encode language data which is an incredibly lossy description of reality. And this line of logic flies against the ground truth reality of the fact that LLMs ARE trained with video and pictures which are essentially photons encoded into data. So what should be the proper conclusion? Well look at the generated visual output of LLMs. These models can generate video that is highly convincing and often with flaws as well but often these videos are indistinguishable from reality. That means the models have very well done but flawed simulations of reality. In fact those videos demonstrate that LLMs have extremely high causal understanding of reality. They know cause and effect it’s just the understanding is imperfect. They understand like 85 percent of it. Just look at those videos of penguins on trampolines. The LLM understands what happens as an effect after a penguin jumps on a trampoline but sometimes an extra penguin teleports in which shows that the understanding is high but not fully accurate or complete.
- LarsDu88 1y agoThe workings of a human eye versus a webcam is mostly an implementation detail IMO and has nothing important to say about what underlies "intelligence" or "world models" It's like saying a component video out cable for the SNES is intrinsically different from an HDMI for putting an image on a screen. They are different, yes, but the outcome we care about is the same. As for causality, go and give a frontier level LLM a simple counterfactual scenario. I think 4/5 will be able to answer correctly or reasonably for most basic cases. I even tried this exercise on some examples from Judea Pearl's 2018 book, "The Book of Why". The fact that current LLMs can tackle this sort of stuff is strongly indicative of there being a decent world model locked inside many of these language models.
- manoDev 1y agoThat’s a good definition: it’s a model of a model. It seems the debate seems to center around whether language models are meta-models (in the category sense) or mere encodings (information theory)?
- StopDisinfo910 1y agoEntities equiped with two limited light sensitive captors encode through a network of carbon based chemical emitters a representation of what its flawed vision system manages to grasp biased towards self preservation. What's the real world? I'm still puzzled by this reaction I see to LLM, not because I think LLM are undervalued, because most people seem to significantly overestimate what is human intelligence.
- wan23 1y agoPhotons reflected off of objects are not the actual objects. I wouldn't go so far as to say that sensing these is a particularly special way to know about things compared to hearing or reading about them. Further, many humans do not sense photons yet seem to manage to have perfectly fine working world models.