fne8w2ah@lemmy.world to Technology@lemmy.worldEnglish · 1 year agoOpenAI confirms that AI writing detectors don’t workarstechnica.comexternal-linkmessage-square109fedilinkarrow-up1703arrow-down133cross-posted to: globalnews@lemmy.zip
arrow-up1670arrow-down1external-linkOpenAI confirms that AI writing detectors don’t workarstechnica.comfne8w2ah@lemmy.world to Technology@lemmy.worldEnglish · 1 year agomessage-square109fedilinkcross-posted to: globalnews@lemmy.zip
minus-squaresebi@lemmy.worldlinkfedilinkEnglisharrow-up2arrow-down3·1 year agoBecause generative Neural Networks always have some random noise. Read more about it here
minus-squarestevedidWHAT@lemmy.worldlinkfedilinkEnglisharrow-up3·1 year agoIsn’t that article about GANs? Isn’t GPT not a GAN?
minus-squarePetDinosaurs@lemmy.worldlinkfedilinkEnglisharrow-up7arrow-down2·1 year agoIt almost certainly has some gan-like pieces. Gans are part of the NN toolbox, like cnns and rnns and such. Basically all commercial algorithms (not just nns, everything) are what I like to call “hybrid” methods, which means keep throwing different tools at it until things work well enough.
minus-squarestevedidWHAT@lemmy.worldlinkfedilinkEnglisharrow-up3·edit-21 year agoThe findings were for GAN models, not GAN like components though.
minus-squarebioemerl@kbin.sociallinkfedilinkarrow-up2·1 year agoIt’s not even about diffusion models. Adversarial networks are basically obsolete
Because generative Neural Networks always have some random noise. Read more about it here
Isn’t that article about GANs?
Isn’t GPT not a GAN?
It almost certainly has some gan-like pieces.
Gans are part of the NN toolbox, like cnns and rnns and such.
Basically all commercial algorithms (not just nns, everything) are what I like to call “hybrid” methods, which means keep throwing different tools at it until things work well enough.
The findings were for GAN models, not GAN like components though.
It’s not even about diffusion models. Adversarial networks are basically obsolete