James Cameron has reportedly revealed an anti-AI title card will open up Avatar 3, officially titled Avatar: Fire and Ash. The Oscar-winning director shared the news in a Q&A session in New Zealand attended by Twitter user Josh Harding.
Sharing a picture of Cameron at the event, they wrote: “Such an incredible talk. Also, James Cameron revealed that Avatar: Fire and Ash will begin with a title card after the 20th Century and Lightstorm logos that ‘no generative A.I. was used in the making of this movie’.”
Cameron has been vocal in the past abo6ut his feelings on artificial intelligence, speaking to CTV news in 2023 about AI-written scripts. “I just don’t personally believe that a disembodied mind that’s just regurgitating what other embodied minds have said – about the life that they’ve had, about love, about lying, about fear, about mortality – and just put it all together into a word salad and then regurgitate it,” he told the publication. “I don’t believe that’s ever going to have something that’s going to move an audience. You have to be human to write that. I don’t know anyone that’s even thinking about having AI write a screenplay.”
All Turing-complete modes of computation are isomorphic so binary or not is irrelevant. Both silicon computers and human brains are Turing-complete, both can compute all computable functions (given enough time and scratch paper).
If non-determinism even exists in the real world (it clashes with cause and effect in a rather fundamental manner) then the architecture of brains, nay the life we know in general, actively works towards minimising its impact. Like, copying the genome has a quite high error rate at first, then error correction is applied which brings the error rate down to practically zero, then randomness is introduced in strategic places, influenced by environmental factors. When the finch genome sees that an individual does not get enough food it throws dice at the beak shape, not mitochondrial DNA.
It’s actually quite obvious in AI models: The reason we can quantise them, essentially rounding every weight of the model to be able to run them with lower-precision maths so they run faster and with less memory, is because the architecture is ludicrously resistant to noise, and rounding every number is equivalent to adding noise, from the perspective of the model.