171–180 of 544 posts
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Anthropic blocks Fable from answering "Tell me about Agent Orange" or even "Tell me about mitochondria"
Putting aside whether or not I agree with the policy or whether it’s at all reasonable, a policy of restricting access to information because there’s a fear it could be used to create a weapon of mass destruction seems entirely different than restricting access to historical facts because they are embarrassing to the government.
Is there any indication of what compute resources this will actually require (in its various incarnations)? Does it incorporate any of the optimisations pioneered by Google (such as TurboQuant, MTP) or some other original innovations to make the frontier quality realistically available to local users?
The GLM-5 series is 744B-A40B. This is not a local model for any reasonable definition of local, but it's an open model which means (once they upload the weights in a week or so) there will be a dozen third-party inference providers competing on price per token.
In the last few days, Chinese labs have given us MiniMaxM3, KimiK2.7 and now GLM5.2. Meanwhile US is censoring models. Reads like fiction.
The Chinese models are censored (too?). > US is censoring models For the current Anthropic issue, I’d say that’s more likely to just be generic corruption, revenge, shakdeown, and/or incompetence from the Trump admin. ‘Censoring’ might be technically correct, but I think one of the aforementioned verbs is a better fit.
It’s not like the American regime is anti-censorship but pro-shakedown.
It's great that we are getting so many open source model releases, but I just feel like SOTA models will always be in the hands of the big players. The hardware requirement to achieve SOTA are just too steep. My alternate universe would involve some sort of decentralized investing scheme to build data centers running massive open source models that could compete on some level with Anthropic, OpenAI, etc.
Do we really care about this gap? If open models are 6 months to a year behind frontier models, does it really matter that much?
Is it a coincidence that both MiniMax and Z.ai are releasing frontier open weights models right as the USG is trying to impose a cap on model capability offered to the public?
No, Dario became too tiresome and annoying that someone had to do something. Personally I hope they ban Opus too. It will only provide more support for open models development. Compare Dario horror posts with this from GLM release: “ Intelligence should be open, accessible, and ready to build with, empowering every developer, everywhere.”
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No, not really. This has been telegraphed for a long time by everyone involved. HN denizens have been unashamedly anti-ai for years now, so what makes sense is the not knowing part of this audience. Chinese models are also not frontier models.
I still find it baffling how the idea that HN is "unashamedly anti-ai" gets repeated. Every single model release gets submitted within minutes of an announcement and frequently break 1000+ points within an hour or two. Blog posts about vibe coding or the current flavor of harness/workflow/tool are constantly making the front page. Karpathy's latest writing/presentations or "Learn how LLMs work using X" are perennial…
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Curious what people's experience is with these models. Anecdotally I tried these out earlier in the year and found it struggled with pretty basic full-stack coding I was doing, when Sonnet 4.6 and Haiku 4.5 didn't break a sweat. Was hoping to use it while my Claude usage was resetting but was disappointed.