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This is the difference between the law and the spirit of the law. Copyright is there to incentivize creation and innovation, and the large-scale use of AI might

This is the difference between the law and the spirit of the law. Copyright is there to incentivize creation and innovation, and the large-scale use of AI might reasonably go against this incentive. The law doesn't exist in a vacuum where is it the word of god and We Have To Obey It. It has a purpose, and we can choose to adapt it to better suit our needs. A note : RNG means it's random. An LLM's output is not random, it's based on previously look-at data (which is the same way humans function, if we're being honest).

slg 3y ago
>The law doesn't exist in a vacuum where is it the word of god and We Have To Obey It. It has a purpose, and we can choose to adapt it to better suit our needs. And this is why this agreement is so important for the future of AI even though it is really only governs movies and TV. Hollywood is a major political force. We all know the story about how Disney has repeatedly pushed for extensions on the life of copyrights. This deal will likely give us good indication into how active and in what areas Hollywood will participate in shaping the law around AI.
Karellen 3y ago
> An LLM's output is not random, it's based on previously look-at data Just because the set of tokens that are considered to be output next have weighted probabilities, does not mean the one selected isn't "random".
- Timon3 3y ago
  How is the selected token "random" if it's chosen based on weighted probabilities, especially if you use a temperature of 0?
  - Karellen 3y ago
    Because even with weighted probabilities, they're still probabilities. If you have "the cat sat on the", and the next possible tokens are "mat" with a probability of 90%, "floor" with a probability of 9%, and "dog" at 1%, how are you going to pick "mat" 90% of the time without consulting a (P)RNG?
    - Timon3 3y ago
      They are only probabilities if you treat them as such. If you always just pick the highest probability option (temperature = 0), it's not random in any way - then it's just a confidence value. You can use randomness, but it's in no way inherent to the process.
      - Karellen 3y ago
        > If you always just pick the highest probability option (temperature = 0), it's not random in any way Huh. That feels like a recipe for either outputting parts of the training data verbatim, or getting stuck in an output loop. Although I earlier gave an example with 90/9/1 weights where the obvious choice is significantly higher than the others, I'd have thought that in a different scenario where you have, say, 51/49 or 34/33/32 options to choose from, always picking the one with only a fractionally higher confidence than the reasonable alternatives could lead to a "sameyness" in the outputs. Isn't there any value in having variance in the generated responses?
        Timon3 3y ago
        > Isn't there any value in having variance in the generated responses? Sure, which is why the technique is used. But that doesn't mean "random" is a useful descriptor. I, as a human, try to add variance to my responses as well - does that mean my mind is "random"? That's why my point is that there is no inherent randomness in the process. We use a bit of randomness to make it subjectively better, but it's fundamentally not random.

slg 3y ago

>The law doesn't exist in a vacuum where is it the word of god and We Have To Obey It. It has a purpose, and we can choose to adapt it to better suit our needs. And this is why this agreement is so important for the future of AI even though it is really only governs movies and TV. Hollywood is a major political force. We all know the story about how Disney has repeatedly pushed for extensions on the life of copyrights. This deal will likely give us good indication into how active and in what areas Hollywood will participate in shaping the law around AI.

Karellen 3y ago

> An LLM's output is not random, it's based on previously look-at data Just because the set of tokens that are considered to be output next have weighted probabilities, does not mean the one selected isn't "random".

Timon3 3y ago
How is the selected token "random" if it's chosen based on weighted probabilities, especially if you use a temperature of 0?
- Karellen 3y ago
  Because even with weighted probabilities, they're still probabilities. If you have "the cat sat on the", and the next possible tokens are "mat" with a probability of 90%, "floor" with a probability of 9%, and "dog" at 1%, how are you going to pick "mat" 90% of the time without consulting a (P)RNG?
  - Timon3 3y ago
    They are only probabilities if you treat them as such. If you always just pick the highest probability option (temperature = 0), it's not random in any way - then it's just a confidence value. You can use randomness, but it's in no way inherent to the process.
    - Karellen 3y ago
      > If you always just pick the highest probability option (temperature = 0), it's not random in any way Huh. That feels like a recipe for either outputting parts of the training data verbatim, or getting stuck in an output loop. Although I earlier gave an example with 90/9/1 weights where the obvious choice is significantly higher than the others, I'd have thought that in a different scenario where you have, say, 51/49 or 34/33/32 options to choose from, always picking the one with only a fractionally higher confidence than the reasonable alternatives could lead to a "sameyness" in the outputs. Isn't there any value in having variance in the generated responses?
      - Timon3 3y ago
        > Isn't there any value in having variance in the generated responses? Sure, which is why the technique is used. But that doesn't mean "random" is a useful descriptor. I, as a human, try to add variance to my responses as well - does that mean my mind is "random"? That's why my point is that there is no inherent randomness in the process. We use a bit of randomness to make it subjectively better, but it's fundamentally not random.