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Comment on Perplexity open sources R1 1776, a version of the DeepSeek R1 model that CEO Aravind Srinivas says has been “post-trained to remove the China censorship”.

FrankLaskey@lemmy.ml ⁨2⁩ ⁨days⁩ ago

I think we can all agree that modifications to these models which remove censorship and propaganda on behalf of one particular country or party is valuable for the sake of accuracy and impartiality, but reading some of the example responses for the new model I honestly find myself wondering if they haven’t gone a bit further than that by replacing some of the old non-responses and positive portrayals of China and the CPC with a highly critical perspective typified by western governments which are hostile to China (in particular the US).

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ZILtoid1991@lemmy.world ⁨2⁩ ⁨days⁩ ago
LLMs are gigantic bias reproduction machines, so it will never be perfect.

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iopq@lemmy.world ⁨2⁩ ⁨days⁩ ago
What part is highly critical of China? Facts can’t be critical

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- fruitycoder@sh.itjust.works ⁨2⁩ ⁨days⁩ ago
  Listen, I’m highly critical of the CCP, but LLMs aren’t facts machines, they are make text like what they are trained on machines.
  
  They have no grasp of truth, and we can only get some sense of truth of what the average collective text response of its dataset (at best!).
  
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  - iopq@lemmy.world ⁨2⁩ ⁨days⁩ ago
    I’m talking about the example texts
    
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brucethemoose@lemmy.world ⁨2⁩ ⁨days⁩ ago
Well you can merge it with the original model, to any degree, to get any sliding scale of “bias” you want.

Practically, though, I guess that’s not super practical, as very few have the hardware or cash to deploy a custom fill R1 themselves.

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