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Bypass DeepSeek censorship by speaking in hex

(substack.com)
755 points MedadNewman | 1 comments | 31 Jan 25 19:41 UTC | HN request time: 0s | source
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femto ◴[31 Jan 25 21:11 UTC] No.42892058[source]▶
This bypasses the overt censorship on the web interface, but it does not bypass the second, more insidious, level of censorship that is built into the model.

https://news.ycombinator.com/item?id=42825573

https://news.ycombinator.com/item?id=42859947

Apparently the model will abandon its "Chain of Thought" (CoT) for certain topics and instead produce a canned response. This effect was the subject of the article "1,156 Questions Censored by DeepSeek", which appeared on HN a few days ago.

https://news.ycombinator.com/item?id=42858552

Edit: fix the last link

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blackeyeblitzar ◴[31 Jan 25 23:39 UTC] No.42893794[source]▶
I have seen a lot of people claim the censorship is only in the hosted version of DeepSeek and that running the model offline removes all censorship. But I have also seen many people claim the opposite, that there is still censorship offline. Which is it? And are people saying different things because the offline censorship is only in some models? Is there hard evidence of the offline censorship?
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1. gerdesj ◴[01 Feb 25 01:36 UTC] No.42894746[source]▶
This system comes out of China. Chinese companies have to abide with certain requirements that are not often seen elsewhere.

DeepSeek is being held up by Chinese media as an example of some sort of local superiority - so we can imply that DeepSeek is run by a firm that complies completely with local requirements.

Those local requirements will include and not be limited to, a particular set of interpretations of historic events. Not least whether those events even happened at all or how they happened and played out.

I think it would be prudent to consider that both the input data and the output filtering (guard rails) for DeepSeek are constructed rather differently to those that are used by say ChatGPT.

There is minimal doubt that DeepSeek represents a superb innovation in frugality of resources required for its creation (training). However, its extant implementation does not seem to have a training data set that you might like it to have. It also seems to have some unusual output filtering.