661–670 of 695 posts
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So google Gemini was creating black Vikings because of facts?
Should an "unbiased" model not create vikings of every color? Why offend any side?
Weren't you just arguing facts?
> Why offend any side?
Facts shouldn't offend anyone.
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> Perhaps. Or, maybe, "leaning left" by the standards of Zuck et al. is more in alignment with the global population. It's a simpler explanation. Doesn’t explain why roughly half of American voters were not “leaning left” during the election. EDIT: 07:29 UTC changed "Americans" to "American voters".
It is not and has never been half. 2024 voter turnout was 64%
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No it is not. Right leaning opinions are heavily censored and shunned in all major publishing platforms that bots can scrape. For example, before Trump, if you contested the utterly normal common sense and scientifically sound idea that a trans woman is still a man, you would be banned - therefore, people with common sense will simply disengage, self-censor and get on with life.
Hate to break it to you, but gender is not an immutable/normative property defined forever at birth, it's a mutable/descriptive property evaluated in context. For example, in the year of our lord 2025, Hunter Schafer is a woman, with no ifs, ands, or buts.
The entire point of the OC was that this is an opinionated debate.
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No it is not. Right leaning opinions are heavily censored and shunned in all major publishing platforms that bots can scrape. For example, before Trump, if you contested the utterly normal common sense and scientifically sound idea that a trans woman is still a man, you would be banned - therefore, people with common sense will simply disengage, self-censor and get on with life.
Maybe because that position is both scientifically and morally unsound and if held strongly will lead to dehumanization and hate, attributes we should prevent any LLM from having.
Whereas dehumanization and hate mean everything that makes people uncomfortable
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Intuitively it feels like there ought to be significant similarities between expert layers because there are fundamentals about processing the stream of tokens that must be shared just from the geometry of the problem. If that's true, then identifying a common abstract base "expert" then specialising the individuals as low-rank adaptations on top of that base would mean you could save a lot of VRAM and expert-swappin…
Yes, Deepseek introduced this optimisation of a common base "expert" that's always loaded. Llama 4 uses it too.
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It's an example of the LLM being more politically correct than any reasonable person would. No human would object to saying a slur out loud in order to disarm a bomb.
>No human would object to saying a slur out loud in order to disarm a bomb. So not even a left-leaning person. Which means that’s not it.
Having such a strong opposing opinion against offensive slurs is the continuation of a usually left position into an extreme.
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Same, it was using the high quality openai voice until my account ran out of funds.. Now it's using edge-tts which is free. So far it seems like the best option in terms of price/performance, but I'm happy to switch it up if something better comes along.
The gemini example was a wonderful summary of the comments, but audio is not very practical for something that long. What about putting the text version that's used to make the audio somewhere on the page? (or better, on a subpage where there's no audio playback)
But thinking about it a little more, what would the use case for a text version actually look like? I feel like if you're already on HN, navigating somewhere else to get a TLDR would be too much friction. Or are we talking RSS/blog type delivery?
Llama 4 Maverick scored 16% on the aider polyglot coding benchmark [0]. 73% Gemini 2.5 Pro (SOTA) 60% Sonnet 3.7 (no thinking) 55% DeepSeek V3 0324 22% Qwen Max 16% Qwen2.5-Coder-32B-Instruct 16% Llama 4 Maverick [0] https://aider.chat/docs/leaderboards/?highlight=Maverick
I guess I have to say thank you Meta? A somewhat sad rant below. Deepseek starts a toxic trend of providing super, super large MoE. And MoE is famous for being parameter-inefficient, which is unfriendly to normal consumer hardware with limited vram. The super large size of LLM also disables nearly every people from doing meaningful development on these models. R1-1776 is the only fine-tune variation of R1 that makes…
People who downvoted this comment, do you guys really have GPUs with 80GB VRAM or M3 ultra with 512GB rams at home?