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The way i understand it is that Sora is mostly just 'moving pictures' with no rhyme or reason. Yann Lecun is interested in videos that tell a 'story', with cau

The way i understand it is that Sora is mostly just 'moving pictures' with no rhyme or reason. Yann Lecun is interested in videos that tell a 'story', with cause and effect. Like a magician putting his hand into a top hat and pulling out a rabbit, kind of video.

throw310822 3y ago
Yeah, the same way ChatGPT is only predicting the next word with no rhyme or reason. However to actually predict the next word so that the entire sentence makes sense and is relevant for the context (e.g. answers a question) you probably must be actually understanding the meaning of the words and the language and have a world model. I can't imagine a NN moving around pixels in the shape of a cat with no understanding whatsoever of what a cat is, what it can do, how it is supposed to move, what it wants, etc.
- justanotherjoe 3y ago
  Of course. But stable diffusion can do that. It understands what a cat is and can draw cat wearing a hat. Videos are about actions, cause and effect, which is entirely different thing than still pictures.
  - throw310822 3y ago
    Well, we definitely see actions, and actors, and causes and effects in the SORA demo videos. With imperfections and occasional mistakes, but they're undeniably there.
  - dkjaudyeqooe 3y ago
    It doesn't understand a cat at all. Humans understand, models are deterministic functions with some randomness added in. Just because it appears to understand doesn't make it so.
    - deleted 3y ago
      [deleted]
    - justanotherjoe 3y ago
      diffusion models can reliably draw a cat when prompted a cat and given a random noise. Sure it's deterministic, but it can work with any random noise in a explorative kind of way. I'd say it's very general in it's 'understanding' of a cat.
      - TheOtherHobbes 3y ago
        It has no "understanding" of a cat. It's an associative store with soft edges that pulls out compressed cat representations when given the noun "cat". The key store includes nouns, adverbs, verbs, and adjectives, and style abstractions, and there are mappings into the store that link all of those. But they're very limited, and if you prompt with a relationship that isn't defined you get best-guess, which will either be quite distant or contaminated with other values. If you ask Dall-E for "a woman made of birds" you get a composite that also includes trees and/or leaves. Dall-E has values for "made of" and "birds" but its value representation for "birds" is contaminated with contextual trees and branches. Leonardo doesn't have a value for "made of", so you get a woman surrounded by bird-like blobs. To understand a cat in a human sense the store would have to include the shape, the movement dynamics in all possible situations, the textures, and a set of defining behaviours that is as complete as possible. It would also have to be able to provide and remember an object-constant instantiation of a specific cat that is clean of contamination. SORA is maybe 10% of the way there. One of the examples doing the rounds shows some puppies playing in snow. It looks impressive until you realise the puppies are zombies. They have none of the expressions or emotions of a real puppy. None of this is impossible, but training time, storage, and power consumption all explode the more information you try to include.
        throw310822 3y ago
        > It's an associative store with soft edges that pulls out compressed cat representations when given the noun "cat". And how do you know that this is not what "understanding" is? To me, understanding the concept of a cat is exactly to immediately recall (or have ready) all the associations, the possibilities, the consequences of the "cat" concept. If you can make up correct sentences about cats and conduct a reasonable conversation about cats, it means that you understand cats.
vasco 3y ago
Did you see the bling zoo demo? How can you say it doesn't have rhyme or reason?
hackerlight 3y ago
I want him to answer how Sora can do water simulations without having a model of part of physics. How can Sora predict where the waves and ripples should go? Is it just "correlations not causal", whatever that means.
- gtirloni 3y ago
  Generative AI is already full of misunderstandings. From people claiming it "understands" to now that it "simulates". I'm no math wiz and my training in statistics is severely lacking but it feels like people need to review what they think it's possible with Generative AI because we are so far from understanding and AGI that my head hurts every time these words show up in a discussion.
  - hackerlight 3y ago
    Geoffrey Hinton and Yoshua Bengio says it can understand and we are close to AGI. Maybe you can explain why they're wrong instead of just saying it.
    - gtirloni 3y ago
      Extraordinary claims require extraordinary proof. I'm not the one making the claims.

throw310822 3y ago

Yeah, the same way ChatGPT is only predicting the next word with no rhyme or reason. However to actually predict the next word so that the entire sentence makes sense and is relevant for the context (e.g. answers a question) you probably must be actually understanding the meaning of the words and the language and have a world model. I can't imagine a NN moving around pixels in the shape of a cat with no understanding whatsoever of what a cat is, what it can do, how it is supposed to move, what it wants, etc.

justanotherjoe 3y ago
Of course. But stable diffusion can do that. It understands what a cat is and can draw cat wearing a hat. Videos are about actions, cause and effect, which is entirely different thing than still pictures.
- throw310822 3y ago
  Well, we definitely see actions, and actors, and causes and effects in the SORA demo videos. With imperfections and occasional mistakes, but they're undeniably there.
- dkjaudyeqooe 3y ago
  It doesn't understand a cat at all. Humans understand, models are deterministic functions with some randomness added in. Just because it appears to understand doesn't make it so.
  - deleted 3y ago
    [deleted]
  - justanotherjoe 3y ago
    diffusion models can reliably draw a cat when prompted a cat and given a random noise. Sure it's deterministic, but it can work with any random noise in a explorative kind of way. I'd say it's very general in it's 'understanding' of a cat.
    - TheOtherHobbes 3y ago
      It has no "understanding" of a cat. It's an associative store with soft edges that pulls out compressed cat representations when given the noun "cat". The key store includes nouns, adverbs, verbs, and adjectives, and style abstractions, and there are mappings into the store that link all of those. But they're very limited, and if you prompt with a relationship that isn't defined you get best-guess, which will either be quite distant or contaminated with other values. If you ask Dall-E for "a woman made of birds" you get a composite that also includes trees and/or leaves. Dall-E has values for "made of" and "birds" but its value representation for "birds" is contaminated with contextual trees and branches. Leonardo doesn't have a value for "made of", so you get a woman surrounded by bird-like blobs. To understand a cat in a human sense the store would have to include the shape, the movement dynamics in all possible situations, the textures, and a set of defining behaviours that is as complete as possible. It would also have to be able to provide and remember an object-constant instantiation of a specific cat that is clean of contamination. SORA is maybe 10% of the way there. One of the examples doing the rounds shows some puppies playing in snow. It looks impressive until you realise the puppies are zombies. They have none of the expressions or emotions of a real puppy. None of this is impossible, but training time, storage, and power consumption all explode the more information you try to include.
      - throw310822 3y ago
        > It's an associative store with soft edges that pulls out compressed cat representations when given the noun "cat". And how do you know that this is not what "understanding" is? To me, understanding the concept of a cat is exactly to immediately recall (or have ready) all the associations, the possibilities, the consequences of the "cat" concept. If you can make up correct sentences about cats and conduct a reasonable conversation about cats, it means that you understand cats.

vasco 3y ago

Did you see the bling zoo demo? How can you say it doesn't have rhyme or reason?

hackerlight 3y ago

I want him to answer how Sora can do water simulations without having a model of part of physics. How can Sora predict where the waves and ripples should go? Is it just "correlations not causal", whatever that means.

gtirloni 3y ago
Generative AI is already full of misunderstandings. From people claiming it "understands" to now that it "simulates". I'm no math wiz and my training in statistics is severely lacking but it feels like people need to review what they think it's possible with Generative AI because we are so far from understanding and AGI that my head hurts every time these words show up in a discussion.
- hackerlight 3y ago
  Geoffrey Hinton and Yoshua Bengio says it can understand and we are close to AGI. Maybe you can explain why they're wrong instead of just saying it.
  - gtirloni 3y ago
    Extraordinary claims require extraordinary proof. I'm not the one making the claims.