this post was submitted on 28 Jul 2023
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Predictable issue if you knew the fundamental technology that goes into these models. Hell it should have been obvious it was headed this way to the layperson once they saw the videos and heard the audio.
We're less sensitive to patterns in massive data, the point at which we cant tell fact from ai fiction from the content is before these machines can't tell. Good luck with the FB aunt's.
GANs final goal is to develop content that is indistinguishable... Are we surprised?
Edit since the person below me made a great point. GANs may be limited but there's nothing that says you can't setup a generator and detector llm with the distinct intent to make detectors and generators for the sole purpose of improving the generator.
For laymen who might not know how GANs work:
Two AI are developed at the same time. One that generates and one that discriminates. The generator creates a dataset, it gets mixed in with some real data, then that all of that gets fed into the discriminator whose job is to say "fake or not".
Both AI get better at what they do over time. This arms race creates more convincing generated data over time. You know your generator has reached peak performance when its twin discriminator has a 50/50 success rate. It's just guessing at that point.
There literally cannot be a better AI than the twin discriminator at detecting that generator's work. So anyone trying to make tools to detect chatGPT's writing is going to have a very hard time of it.
Tx!