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> I know that humans have intentionality and agency. You assume that. You can only maybe know that about yourself. But my question was bit different. How do yo

by m4nu3l 4y ago

> I know that humans have intentionality and agency. You assume that. You can only maybe know that about yourself. But my question was bit different. How do you know that the ML model doesn't? > about topics for which they have no prior information, by applying reasonable similarities. This is a contradiction. If you have no prior information about a topic you can't know even what topic is similar. > Even if someone never heard the phrase "walking a mile in someone elses shoes". Same for ML modes. They don't have a representation of every possible prompt.

usrbinbash 4y ago
> You assume that. You can only maybe know that about yourself. I can also only say with certainty that planetary gravity is an attracting force on the very spot I am standing on. I haven't visited every spot on every planet in the universe after all. That doesn't make it any more likely that my extrapolation of how gravity works here is wrong somewhere else. Russels Teapot works both ways. > How do you know that the ML model doesn't? For the same reason why I know that a Hammer or an Operating System don't. I know how they work. Not in the most minute details, and of course the actual model is essentially a black box, but it's architecture, and MO are not. It completes sequences. That is all it does. It has no semantic understanding of the things these sequences represent. It has no understanding of true or false. It doesn't know math, it doesn't know who person xyz is, it doesn't know that 1993 already happened and 2221 did not. It cannot have abstract concepts of the things represented by the sequences, because the sequences are the things in its world. It knows that a sequence is more or less likely to follow another sequence. That's it. From that limited knowledge however, it can very successfully mimick things like math, logic, and even reasoning to an extend. And it can mimick them well enough to be useful in a lot of areas. But that mimickry, however useful, is still mimickry. It's still the Chinese-Room thought experiment.

by m4nu3l 4y ago

usrbinbash 4y ago

> You assume that. You can only maybe know that about yourself. I can also only say with certainty that planetary gravity is an attracting force on the very spot I am standing on. I haven't visited every spot on every planet in the universe after all. That doesn't make it any more likely that my extrapolation of how gravity works here is wrong somewhere else. Russels Teapot works both ways. > How do you know that the ML model doesn't? For the same reason why I know that a Hammer or an Operating System don't. I know how they work. Not in the most minute details, and of course the actual model is essentially a black box, but it's architecture, and MO are not. It completes sequences. That is all it does. It has no semantic understanding of the things these sequences represent. It has no understanding of true or false. It doesn't know math, it doesn't know who person xyz is, it doesn't know that 1993 already happened and 2221 did not. It cannot have abstract concepts of the things represented by the sequences, because the sequences are the things in its world. It knows that a sequence is more or less likely to follow another sequence. That's it. From that limited knowledge however, it can very successfully mimick things like math, logic, and even reasoning to an extend. And it can mimick them well enough to be useful in a lot of areas. But that mimickry, however useful, is still mimickry. It's still the Chinese-Room thought experiment.