4 ms·

This post is full of speculation. For starters, human minds do more than just language. There are some arguments (Moravec's paradox) that posit that language is

This post is full of speculation. For starters, human minds do more than just language. There are some arguments (Moravec's paradox) that posit that language is easy, while keeping the rest of the body working is the real hard problem. I've yet to see an humanoid robot controlled by an LLM that can tackle difficult physical problems like riding a bike or skiing in for the first time real-time, just as humans, that need to coordinate at least 5 senses (some say up to 20 but I digress) plus emotions and a train of thought to do so. Plus, sure, LLMs are simpler (that only works if you don't count the full complexity of its substrate: a lot of GPUs, interconnects, Data Centers, etc), yet they consume an insane amount of energy and matter when compared to humans. It is surprising that LLMs are so capable, but for 2000kcal a day humans are still more impressive to me. People see a model dominating language and start thinking the only thing humans do is high-level language and reasoning. That may be why the brilliant minds of this decade talk about replacing white-collars, but no plate-cleaning bot in sight. Metacommentary: a lot of LLM-human equality apologists seem to have little knowledge of the AI field and its history, as these themes are not new at all.

ben_w 2y ago
> For starters, human minds do more than just language. These days, so do the AI (even though these ones are still called LLMs, which I think is now a bad name even though I continue to use the term without always being mindful of this). > I've yet to see an humanoid robot controlled by an LLM that can tackle difficult physical problems like riding a bike or skiing in for the first time real-time, just as humans, that need to coordinate at least 5 senses (some say up to 20 but I digress) plus emotions and a train of thought to do so. 1) I'd agree that AI are slow learners (as measured by number of examples rather than wall clock). For me, this is more significant than the difference in wattage. 2) 13 years ago, before the Transformer model: https://www.youtube.com/watch?v=mT3vfSQePcs https://www.youtube.com/watch?v=mT3vfSQePcs 3) We don't use 5 senses to ride a bike; I can believe touch, vision, proprioception, and balance are all involved, but that's only 4. Why would hearing, smell, or taste be involved? For emotion, my weakly-held belief is that this is what motivates us and tells us what the concept of "good" even is — i.e. it doesn't give us reasoning beyond being a motivation to learn to reason. > It is surprising that LLMs are so capable, but for 2000kcal a day humans are still more impressive to me. Our biological energy efficiency sure is nice, though progress with silicon is continuing even if the rate of improvement is decreasing: https://en.wikipedia.org/wiki/Koomey%27s_law https://en.wikipedia.org/wiki/Koomey%27s_law That said, I don't consider the substrate efficiency to be an indication of if the thing running on it is or isn't "reasoning" — if the same silicon was running a quantum chemistry simulation of the human brain it would be an even bigger power hog and yet I would say it "must be" reasoning, and conversely we use phrases such "turn your brain off and enjoy" to describe categories of film where the plot holes become pot holes if you stop to think about them (the novel I'm trying to write is due to me being nerd-sniped in this way by everything wrong with Independence Day). > That may be why the brilliant minds of this decade talk about replacing white-collars, but no plate-cleaning bot in sight. I mean, I've got a dishwasher already… ;) But more seriously, even though I'm getting cynical about press releases that turn out to be smoke and mirrors, (humanoid) robots doing housework is "in sight" in at least the same kind of way as self driving cars (which has been a decade of "next year honest" mirages, so I'm not giving a timeline): https://www.youtube.com/watch?v=Sq1QZB5baNw https://www.youtube.com/watch?v=Sq1QZB5baNw > Metacommentary: a lot of LLM-human equality apologists seem to have little knowledge of the AI field and its history, as these themes are not new at all. I've been feeling the same, but on both sides, pro and con. The Turing paper laid out all the same talking points I've been seeing over the last few years, and those talking points weren't new when he wrote them down.
- mrbungie 2y ago
  1. For me transformer multimodal processing is still language, as the work is done via tokens/patches. In fact, that makes its image processing capabilities limited in some scenarios when compared to other techniques. 2. When on a bike you need to be full alert and hearing all the time or you might provoke an accident. Sure you can use headphones, but it is not recommended. Also, that robot you showed is narrow AI, it should be out of discussion when arguing about complex end-to-end models that are supposedly comparable to humans. If not, we could just code any missing capability as a tool, but that would automatically invalidate the "llms reason/think/process the same way as humans" argument. 3. Agree, I expect the same in the future. I'm talking about the present though. 4. ;) a robot that helps with daily chores can't come soon enough. More important than coding AI for me. PS: Not sure if we're talking about the same argument anymore, I'm following the line of "LLMs work/reason the same as humans" not "AI can't perform as good as humans (now and in the future)"
  - ben_w 2y ago
    > PS: Not sure if we're talking about the same argument anymore, I'm following the line of "LLMs work/reason the same as humans" not "AI can't perform as good as humans (now and in the future)" Yeah, it's hard to keep track :) I think we're broadly on the same page with all of this, though. (Even if I might be a little more optimistic on tokenised processing of images).
- Jensson 2y ago
  > For emotion, my weakly-held belief is that this is what motivates us and tells us what the concept of "good" even is — i.e. it doesn't give us reasoning beyond being a motivation to learn to reason. I've found I work differently. Some technical problems like architecture can only be solved by aligning my emotions with the problem, then my primal brains find a good solution that matches my emotional wants. But when my emotions doesn't care about the problem my intuition stops working to solve it, and then I can't find any solution. Why would emotions be needed to solve problems? Because without emotions your can't navigate a complex solution space to find a good solution, its impossible. Meaning if we want an AI to make good architecture for example, we would need to make the AI have feelings about architecture such as what setups are good in different situation etc. Without those feelings the AI wouldn't be able to solve the problem well. Then after you have came up with a solution using emotions you can then verify it using logic, but you wouldn't have came up with that solution in the first place without using your emotions. Hence emotions are probably needed for truly intelligent reasoning, as otherwise you can't properly guide yourself through complex solution spaces. You could code something that fills the same role and call it something different than emotions, but if it works the same way and fills the same functions its still emotions. (Using this definition then AlphaGo uses emotions to prune board states to check, stuff like that, it doesn't know those states are best to check, its just a feeling it has)
ninetyninenine 2y ago
There is no speculation. The speculation was added by your own imagination. The LLM and human brain are neural nets. No speculation here, the statement is true despite what you said.

ben_w 2y ago

> For starters, human minds do more than just language. These days, so do the AI (even though these ones are still called LLMs, which I think is now a bad name even though I continue to use the term without always being mindful of this). > I've yet to see an humanoid robot controlled by an LLM that can tackle difficult physical problems like riding a bike or skiing in for the first time real-time, just as humans, that need to coordinate at least 5 senses (some say up to 20 but I digress) plus emotions and a train of thought to do so. 1) I'd agree that AI are slow learners (as measured by number of examples rather than wall clock). For me, this is more significant than the difference in wattage. 2) 13 years ago, before the Transformer model: https://www.youtube.com/watch?v=mT3vfSQePcs https://www.youtube.com/watch?v=mT3vfSQePcs 3) We don't use 5 senses to ride a bike; I can believe touch, vision, proprioception, and balance are all involved, but that's only 4. Why would hearing, smell, or taste be involved? For emotion, my weakly-held belief is that this is what motivates us and tells us what the concept of "good" even is — i.e. it doesn't give us reasoning beyond being a motivation to learn to reason. > It is surprising that LLMs are so capable, but for 2000kcal a day humans are still more impressive to me. Our biological energy efficiency sure is nice, though progress with silicon is continuing even if the rate of improvement is decreasing: https://en.wikipedia.org/wiki/Koomey%27s_law https://en.wikipedia.org/wiki/Koomey%27s_law That said, I don't consider the substrate efficiency to be an indication of if the thing running on it is or isn't "reasoning" — if the same silicon was running a quantum chemistry simulation of the human brain it would be an even bigger power hog and yet I would say it "must be" reasoning, and conversely we use phrases such "turn your brain off and enjoy" to describe categories of film where the plot holes become pot holes if you stop to think about them (the novel I'm trying to write is due to me being nerd-sniped in this way by everything wrong with Independence Day). > That may be why the brilliant minds of this decade talk about replacing white-collars, but no plate-cleaning bot in sight. I mean, I've got a dishwasher already… ;) But more seriously, even though I'm getting cynical about press releases that turn out to be smoke and mirrors, (humanoid) robots doing housework is "in sight" in at least the same kind of way as self driving cars (which has been a decade of "next year honest" mirages, so I'm not giving a timeline): https://www.youtube.com/watch?v=Sq1QZB5baNw https://www.youtube.com/watch?v=Sq1QZB5baNw > Metacommentary: a lot of LLM-human equality apologists seem to have little knowledge of the AI field and its history, as these themes are not new at all. I've been feeling the same, but on both sides, pro and con. The Turing paper laid out all the same talking points I've been seeing over the last few years, and those talking points weren't new when he wrote them down.

mrbungie 2y ago
1. For me transformer multimodal processing is still language, as the work is done via tokens/patches. In fact, that makes its image processing capabilities limited in some scenarios when compared to other techniques. 2. When on a bike you need to be full alert and hearing all the time or you might provoke an accident. Sure you can use headphones, but it is not recommended. Also, that robot you showed is narrow AI, it should be out of discussion when arguing about complex end-to-end models that are supposedly comparable to humans. If not, we could just code any missing capability as a tool, but that would automatically invalidate the "llms reason/think/process the same way as humans" argument. 3. Agree, I expect the same in the future. I'm talking about the present though. 4. ;) a robot that helps with daily chores can't come soon enough. More important than coding AI for me. PS: Not sure if we're talking about the same argument anymore, I'm following the line of "LLMs work/reason the same as humans" not "AI can't perform as good as humans (now and in the future)"
- ben_w 2y ago
  > PS: Not sure if we're talking about the same argument anymore, I'm following the line of "LLMs work/reason the same as humans" not "AI can't perform as good as humans (now and in the future)" Yeah, it's hard to keep track :) I think we're broadly on the same page with all of this, though. (Even if I might be a little more optimistic on tokenised processing of images).
Jensson 2y ago
> For emotion, my weakly-held belief is that this is what motivates us and tells us what the concept of "good" even is — i.e. it doesn't give us reasoning beyond being a motivation to learn to reason. I've found I work differently. Some technical problems like architecture can only be solved by aligning my emotions with the problem, then my primal brains find a good solution that matches my emotional wants. But when my emotions doesn't care about the problem my intuition stops working to solve it, and then I can't find any solution. Why would emotions be needed to solve problems? Because without emotions your can't navigate a complex solution space to find a good solution, its impossible. Meaning if we want an AI to make good architecture for example, we would need to make the AI have feelings about architecture such as what setups are good in different situation etc. Without those feelings the AI wouldn't be able to solve the problem well. Then after you have came up with a solution using emotions you can then verify it using logic, but you wouldn't have came up with that solution in the first place without using your emotions. Hence emotions are probably needed for truly intelligent reasoning, as otherwise you can't properly guide yourself through complex solution spaces. You could code something that fills the same role and call it something different than emotions, but if it works the same way and fills the same functions its still emotions. (Using this definition then AlphaGo uses emotions to prune board states to check, stuff like that, it doesn't know those states are best to check, its just a feeling it has)

ninetyninenine 2y ago

There is no speculation. The speculation was added by your own imagination. The LLM and human brain are neural nets. No speculation here, the statement is true despite what you said.