ylai@lemmy.ml to Technology@lemmy.worldEnglish · 1 年前VR Headsets Are Approaching the Eye’s Resolution Limitsspectrum.ieee.orgexternal-linkmessage-square32fedilinkarrow-up112arrow-down12
arrow-up110arrow-down1external-linkVR Headsets Are Approaching the Eye’s Resolution Limitsspectrum.ieee.orgylai@lemmy.ml to Technology@lemmy.worldEnglish · 1 年前message-square32fedilink
minus-squareKairuByte@lemmy.dbzer0.comlinkfedilinkEnglisharrow-up1arrow-down2·1 年前 maybe the whole damn thing is outsourced to ChatGPT now, who the fuck knows. I don’t understand why so many people assume an LLM would make glaring errors like this…
minus-squaredrislands@lemmy.worldlinkfedilinkEnglisharrow-up3arrow-down1·1 年前…because they frequently do? Glaring errors are like, the main thing LLMs produce besides hype.
minus-squareKairuByte@lemmy.dbzer0.comlinkfedilinkEnglisharrow-up5arrow-down1·edit-21 年前They make glaring errors in logic, and confidently state things that are not true. But their whole “deal” is writing proper sentences based on predictive models. They don’t make mistakes like the excerpt highlighted.
minus-squareGlitterInfection@lemmy.worldlinkfedilinkEnglisharrow-up1·1 年前Pretty soon glaring errors like this will be the only way to identify human vs LLM writing. Then soon after that the LLMs will start producing glaring grammatical errors to match the humans.
minus-squaredrislands@lemmy.worldlinkfedilinkEnglisharrow-up1·1 年前Y’know what, that’s a fair point. Though I’m not the original commenter from the top, heh.
minus-squareKairuByte@lemmy.dbzer0.comlinkfedilinkEnglisharrow-up2·1 年前Ah apologies, I’m terrible with tracking usernames, I’ll edit for clarity.
minus-squaredrislands@lemmy.worldlinkfedilinkEnglisharrow-up1·1 年前No worries mate. I appreciate the correction regardless.
minus-squareGarbanzo@lemmy.worldlinkfedilinkEnglisharrow-up1·1 年前I’m imagining that the first output didn’t cover everything they wanted so they tweaked it and pasted the results together and fucked it up.
I don’t understand why so many people assume an LLM would make glaring errors like this…
…because they frequently do? Glaring errors are like, the main thing LLMs produce besides hype.
They make glaring errors in logic, and confidently state things that are not true. But their whole “deal” is writing proper sentences based on predictive models. They don’t make mistakes like the excerpt highlighted.
Pretty soon glaring errors like this will be the only way to identify human vs LLM writing.
Then soon after that the LLMs will start producing glaring grammatical errors to match the humans.
Y’know what, that’s a fair point. Though I’m not the original commenter from the top, heh.
Ah apologies, I’m terrible with tracking usernames, I’ll edit for clarity.
No worries mate. I appreciate the correction regardless.
I’m imagining that the first output didn’t cover everything they wanted so they tweaked it and pasted the results together and fucked it up.