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> So the tasks remain useful and accurate in testing ToM in people because people can't perform statistical regressions over billion-token sets and therefore mu
by spuz 4y ago
> So the tasks remain useful and accurate in testing ToM in people because people can't perform statistical regressions over billion-token sets and therefore must generate their thoughts the old fashioned way.
Is it not also possible that the study suggests that the human mind actually operates as a statistical regression over billions of data points rather than through some kind of Baysian logic? You say humans are known to be not-great at statistical next-word guesses, but I would antelope they're actually pretty good at it.
- pdonis 4y ago> Is it not also possible that the study suggests that the human mind actually operates as a statistical regression over billions of data points rather than through some kind of Baysian logic? No. Human minds have semantic relationships to the rest of the world that LLMs do not have. The comparisons being made between the two, not just in this paper but in all of the hype surrounding LLMs, are simply invalid. But they sure help in collecting more funding.
- mietek 4y agoPlease define “semantic relationship”.
- pdonis 4y agoSee my response to strbean upthread.
- mietek 4y agoOkay. It seems to me that, in analogy to humans having such a relationship with physical reality, machine learning systems have such a relationship with virtual reality — the environment in which they are trained and deployed.
- pdonis 4y ago> machine learning systems have such a relationship with virtual reality No, they don't, because they can't take actions in that virtual reality and sense the consequences. They can't test hypotheses about how the reality works. They can't even frame hypotheses about how the reality works.
- spuz 4y agoRight, but some neural networks are trained in virtual 3D physical simulations and are able to apply their knowledge acquired through statistical regression of a simulated world to perform tasks and even make predictions. It's logical that a network trained purely on language has no real understanding of physical reality, but it doesn't preclude that a sense of reality in the way we humans think we have can't be gained by the same statistical analysis of the real world.
- pdonis 4y ago> some neural networks are trained in virtual 3D physical simulations and are able to apply their knowledge acquired through statistical regression of a simulated world to perform tasks and even make predictions As you note, this is very different from using text data as a training set for a language model. I am not familiar enough with this work to comment on it in any detail, but it is not the kind of work I have been addressing in my comments elsewhere in this thread, so my comments should certainly not be taken as any kind of evaluation of what I think this kind of thing is or is not capable of.
- helf 4y agoWait, you mean virtual reality isn’t like the cartoon Reboot!?
- strbean 4y ago> Human minds have semantic relationships to the rest of the world that LLMs do not have. This is a bold claim that seems built on a presumption of mind-body dualism. Brains don't have semantic relationships with anything. They are neurons hooked up to sensors and actuators. Any inferences they produce are the result of statistical processes.
- pdonis 4y ago> This is a bold claim that seems built on a presumption of mind-body dualism. Not at all. I'm a physicalist; I don't believe the mind is a separate thing from the brain. > Brains don't have semantic relationships with anything. Yes, they do: you describe them yourself: > They are neurons hooked up to sensors and actuators. Those are semantic relationships with the rest of the world. Although your short description does not by any means do justice to the complexity and richness of those relationships.
- strbean 4y agoI see what you're saying; ChatGPT doesn't have a physical relationship with the world, doesn't have agency (is essentially paused until given input), doesn't have reward/punishment stimulae, etc. I do think that a large portion of what seems to be missing here is trivial to add, relative to the effort in creating ChatGPT in the first place. Side note: I'm not sure 'semantic relationship' is the right term here. Pretty sure it is specific to relationships between linguistic constructs. That wording very much triggered my "Bah, dualism!" response, as I thought you were insinuating some metaphysical bond between the mind and the world. Maybe "meaningful relationship" would serve better?
- pdonis 4y ago> I do think that a large portion of what seems to be missing here is trivial to add If you really think it's trivial, then do it! I would be interested to see the results of anyone doing this. But there aren't any to see right now. > I'm not sure 'semantic relationship' is the right term here. It might not be; but in the cognitive science literature that term is used for more than just relationships between linguistic constructs; it is used for relationships between internal features of a model or an entity and features of the external world. I think this usage is also common in robotics, and more generally in domains like mechanical engineering which are often concerned with creating software programs to do things like manage fuel and air flow in car engines.
- hackinthebochs 4y ago>Human minds have semantic relationships to the rest of the world that LLMs do not have Can you make this point without stuffing all the hard work into poorly defined words like "semantic relationships"? Until then, I'm not sure the point is intelligible.