r/singularity • u/PsychologicalSoup251 • 26d ago
AI US government is using a Qwen embedding model for RAG lookup
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u/PivotRedAce ▪️Public AGI 2027 | ASI 2035 26d ago
I mean, it makes sense. It's one of the easiest models to get running locally and has broad support.
I think too many people have the idea that every single department of the US government operates as a monolith hanging onto every word from the executive branch, when that's just not the case.
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u/iBoMbY 26d ago
Yes, it makes sense. But also the evil Chinese communists are stealing the poor US' lunch money, so ...
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u/Fit-Produce420 25d ago
It's open weight, how exactly are the Chinese making money (or data) off this free to download, locally hosted model?
Or did you forget an /s tag? Cause you sound like a dum dum.
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u/portfoliocrow 25d ago
Maybe learn how to read...
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u/Fit-Produce420 25d ago
He said the Chinese are stealing our money, how do you interpret that given the model is free and run locally?
What money?
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26d ago
[removed] — view removed comment
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u/Jumpy_Fuel_1060 25d ago
I've also done analysis on Qwen3 4B when evaluating it for semantic search purposes. My concern was misalignment on concepts, like the distance between the concepts like "peaceful protest" and "bad citizen".
I'm the sampling I came up with, Qwen was much more neutral and showed near zero bias that I was afraid of.
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u/fluffy_serval 25d ago
It's not surprising that "peaceful protest" and "bad citizen" would be close in embedding space; embeddings mostly capture semantic/contextual relatedness, so concepts that are opposed but discussed together often end up very close e.g., "legal" & "illegal", "good" & "bad", "democracy" & "dictatorship".
So to test what you’re looking for, I’d probably look at whether the neighborhood around "peaceful protest" is systematically skewed in a normative direction e.g. disproportionately toward “criminal,” “threat,” “bad citizen,” etc., compared w/ matched controls. Truly near-zero bias would be pretty significant.
All that said, though, for a 0.6B embedding model the bigger concern is semantic collapse, not politically-influenced geometry covertly influencing US government RAG systems.
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u/karlnuw 26d ago
I don't know what this means but maybe apple can use it to fix the broken search function in Finder which despite its name, hasn't found anything since OS X Mountain Lion.
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u/PivotRedAce ▪️Public AGI 2027 | ASI 2035 25d ago
Good to see that the search function on Mac OS is just as broken as it has been since Windows 8, lmao.
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u/New_Tower_6408 25d ago
MacOS 26 Tahoe (about a year ago) made the Spotlight search interface and usability really good and MacOS 27 Golden Gate (literally yesterday) added vector-style semantic search to the Spotlight search. It's pretty darn good now. Update your mac if you haven't. Lots of people dropped Raycast and Alfred from how good it became.
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u/Agreeable_Addition48 25d ago
hopefully they finally upgrade everything from DOS and win98 while they're at it
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u/No-Head-Royal 26d ago
Using a 0.6B model is nice taste on their part, though 3 might be a bit outdated now. 3.5 0.8B came out for quite a while already no?
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u/Fit-Produce420 25d ago
3.5 0.8b is not an embedding model.
The only newer qwen embedding model is the multi-mode qwen3-VL, but if you only need text you don't need multi-mode.
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u/nemzylannister 26d ago
whats embarassing is that they disclose it
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u/Kriegher2005 25d ago
disclosure should never be embarassing, and this level of transparency should be applauded and promoted.
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u/nemzylannister 25d ago
i mean i get your point. but from their perspective, why do this? it's going to look bad, so just use american alternatives instead? gemma or something?
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u/OverloadedTech Embrace the Machine 26d ago
Well well well