4 ms·

GPTs are parrots. v4 is much better but still just a parrot. Since humans have yet to figure out the whole process behind brain thinking/intelligence/abstractio

GPTs are parrots. v4 is much better but still just a parrot. Since humans have yet to figure out the whole process behind brain thinking/intelligence/abstractions, then there is no way they can replicate that into machines. And brain is all about chemical reactions - can that be replicated with just 0s and 1s? Sad fact is that many people will think GPT writes something meaningful, while it will always only write something probable. We will be flooded with content that will get harder and harder to prove wrong, but it will be wrong.

lovemenot 4y ago
This argument is imbalanced. Not necessarily wrong. To follow scientific method, you should specify what would be meaningful according to your parameters: not merely parroting. If and when that is achieved by LLMs, instead of moving the goalposts, accept that something genuine has happened. >> We will be flooded with content that will get harder and harder to prove wrong, but it will be wrong. I mostly agree, especially about quantity. But since you wish to draw a line in the sand, define quality. Or truth.
- fl7305 4y ago
  Exactly. Or to put it differently: Is "GPT-4 is just a parrot" a falsifiable claim? If so, what does the test look like that would falsify it?
  - jarek83 4y ago
    I guess debugability will be its most desired feature soon. Let's see what copyrights will do with it.
    - fl7305 4y ago
      What do "debuggability" or "copyrights" have to do with: Is "GPT-4 is just a parrot" a falsifiable claim? If so, what does the test look like that would falsify it? Can you think of questions to test GPT-4s ability to reason that 90% of human 12-year olds will answer correctly, but where GPT-4 constantly struggles?
      - jarek83 4y ago
        Look at my previous comment about a city without a Zoo.
- jarek83 4y ago
  >> But since you wish to draw a line in the sand, define quality. Or truth. I asked it about tourists attractions in a city I know. One of the items it listed was a Zoo. There is no Zoo there. It seemed like it just took the majority of the question into account at some point and ignored the city name itself and since most questions like that are about big cities that have zoos, it went ahead to suggest it, since it was among probable answers. It will get better with more input and will get this kind of obvious questions right. But I believe it will never truly 'know' what it is talking about. And we will start to believe it does.
fl7305 4y ago
> Since humans have yet to figure out the whole process behind brain thinking/intelligence/abstractions, then there is no way they can replicate that into machines. By that logic, humans can't write a superhuman Chess/Go program unless they can articulate the specific algorithms to select the next move. But that's clearly not true. Neural networks have been trained to play superhuman chess just by example. Not by programmers figuring out the whole process behind chess/go playing.
hackinthebochs 4y ago
This is a bad take. It is clear to me that LLMs are capable of a robust sense of understand some in some cases. I go into some detail here: https://www.reddit.com/r/naturalism/comments/1236vzf/on_large_language_models_and_understanding/ https://www.reddit.com/r/naturalism/comments/1236vzf/on_larg...
nuancebydefault 4y ago
Whether LLMs work like brains is irrelevant. GPT writes many meaningful things. Jobs are being replaced by AI as we speak. We are seeing the top of the AI iceberg. How this will end, mostly for the good or mostly for the bad, nobody can tell today. What we can already tell is that this evolution is unstoppable and will change the world to an amount comparable to the emerging of the internet.

lovemenot 4y ago

This argument is imbalanced. Not necessarily wrong. To follow scientific method, you should specify what would be meaningful according to your parameters: not merely parroting. If and when that is achieved by LLMs, instead of moving the goalposts, accept that something genuine has happened. >> We will be flooded with content that will get harder and harder to prove wrong, but it will be wrong. I mostly agree, especially about quantity. But since you wish to draw a line in the sand, define quality. Or truth.

fl7305 4y ago
Exactly. Or to put it differently: Is "GPT-4 is just a parrot" a falsifiable claim? If so, what does the test look like that would falsify it?
- jarek83 4y ago
  I guess debugability will be its most desired feature soon. Let's see what copyrights will do with it.
  - fl7305 4y ago
    What do "debuggability" or "copyrights" have to do with: Is "GPT-4 is just a parrot" a falsifiable claim? If so, what does the test look like that would falsify it? Can you think of questions to test GPT-4s ability to reason that 90% of human 12-year olds will answer correctly, but where GPT-4 constantly struggles?
    - jarek83 4y ago
      Look at my previous comment about a city without a Zoo.
jarek83 4y ago
>> But since you wish to draw a line in the sand, define quality. Or truth. I asked it about tourists attractions in a city I know. One of the items it listed was a Zoo. There is no Zoo there. It seemed like it just took the majority of the question into account at some point and ignored the city name itself and since most questions like that are about big cities that have zoos, it went ahead to suggest it, since it was among probable answers. It will get better with more input and will get this kind of obvious questions right. But I believe it will never truly 'know' what it is talking about. And we will start to believe it does.

fl7305 4y ago

> Since humans have yet to figure out the whole process behind brain thinking/intelligence/abstractions, then there is no way they can replicate that into machines. By that logic, humans can't write a superhuman Chess/Go program unless they can articulate the specific algorithms to select the next move. But that's clearly not true. Neural networks have been trained to play superhuman chess just by example. Not by programmers figuring out the whole process behind chess/go playing.

hackinthebochs 4y ago

This is a bad take. It is clear to me that LLMs are capable of a robust sense of understand some in some cases. I go into some detail here: https://www.reddit.com/r/naturalism/comments/1236vzf/on_large_language_models_and_understanding/ https://www.reddit.com/r/naturalism/comments/1236vzf/on_larg...

nuancebydefault 4y ago

Whether LLMs work like brains is irrelevant. GPT writes many meaningful things. Jobs are being replaced by AI as we speak. We are seeing the top of the AI iceberg. How this will end, mostly for the good or mostly for the bad, nobody can tell today. What we can already tell is that this evolution is unstoppable and will change the world to an amount comparable to the emerging of the internet.