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> That the crucial difference between a human being and AI is that if you show a 3 year old kid one picture of a cat, a kid can recognize all other cats. Have

> That the crucial difference between a human being and AI is that if you show a 3 year old kid one picture of a cat, a kid can recognize all other cats. Have you done this test for real? My nephew calls everything which moves but not a human a "dog". In his world there are flying dogs and swimming dogs. Probably if he would see an elephant that would be a big dog, while a giraffe would be a tall dog. Now obviously he will learn the customary categories, but it is definitely not a one-shot thing. > You can feed ML 5000 pictures of cats and it can recognize a cat in a picture with something like 95% confidence. This is an area of active research. One term of art is "one-shot learning". The general idea is that you show 5 million things to the AI, but none of them are a harumpf, and it learns how "things" are. And then you show it a single image of a harumpf and tell it that it is a harumpf and it will be able to classify things as harumpf or not from then on. How great do these things work? They kinda work, but you can still get a phd for making a better one. So they are not that great. But I wouldn't pin my hat on this one "crucial difference between a human being and an AI", because you might get surprised once humans teach the AIs this trick too.

coldtea 4y ago
>Have you done this test for real? My nephew calls everything which moves but not a human a "dog". In his world there are flying dogs and swimming dogs. Probably if he would see an elephant that would be a big dog, while a giraffe would be a tall dog. As long as he can tell a "tall dog" (giraffe) apart from a "swimming dog" (say, a duck) that's still compatible with what the parent says. It's about recognizing them as distict, and assigning them to the same class of things, the rest is just naming, that is, its at the language and vocabulary level, not at the recognition level.
- dangond 4y ago
  And how many shots does it take for the kid to learn what "swimming" means or what "tall" means?
  - coldtea 4y ago
    Not that many. They can do it at like 2-3, with 1/1000000th the training set, at least words wise.
    - dangond 4y ago
      All the words they have experienced up to that point are part of the training set, as well as all the people and things they have seen.
      - coldtea 4y ago
        Even if people around the 3-year old child talk to it 16 hours per day constantly at 150 words per minute, they'd just have around 1GB of text in its training data. And not good quality words even, a lot of it would be variations of mundane everyday chit chat and "whose a cute baby?! You're a cute baby!". For comparison GPT has like 1TB of text, and they're hundreds of thousands of books, articles, wikipedia, and so on. So already 3 orders of magnitude more. And of course the "16 hours x 150 words per minute x 3 years" is totally off by a few orders of magnitude itself.

coldtea 4y ago

>Have you done this test for real? My nephew calls everything which moves but not a human a "dog". In his world there are flying dogs and swimming dogs. Probably if he would see an elephant that would be a big dog, while a giraffe would be a tall dog. As long as he can tell a "tall dog" (giraffe) apart from a "swimming dog" (say, a duck) that's still compatible with what the parent says. It's about recognizing them as distict, and assigning them to the same class of things, the rest is just naming, that is, its at the language and vocabulary level, not at the recognition level.

dangond 4y ago
And how many shots does it take for the kid to learn what "swimming" means or what "tall" means?
- coldtea 4y ago
  Not that many. They can do it at like 2-3, with 1/1000000th the training set, at least words wise.
  - dangond 4y ago
    All the words they have experienced up to that point are part of the training set, as well as all the people and things they have seen.
    - coldtea 4y ago
      Even if people around the 3-year old child talk to it 16 hours per day constantly at 150 words per minute, they'd just have around 1GB of text in its training data. And not good quality words even, a lot of it would be variations of mundane everyday chit chat and "whose a cute baby?! You're a cute baby!". For comparison GPT has like 1TB of text, and they're hundreds of thousands of books, articles, wikipedia, and so on. So already 3 orders of magnitude more. And of course the "16 hours x 150 words per minute x 3 years" is totally off by a few orders of magnitude itself.