It is entirely possible that the steady-state people will prove to be right in the future, but there's no sign of a slowdown yet. And if greater intelligence brings greater value at an exponential pace (which it has, but may not always) then it matters a lot which world we're in.
AI
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Open models have better dollar per token than closed APIs
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An interesting way to take Noam at his word in regards to always keeping a constant inference budget for any eval reporting –
— swyx @aiDotEngineer WF (@swyx) 27 juin 2026
is that open models have a lot more dollar per token mileage than closed model APIs. So anyone launching an open model today or situationally… https://t.co/vGl7tQZgWnAn interesting way to take Noam at his word in regards to always keeping a constant inference budget for any eval reporting – is that open models have a lot more dollar per token mileage than closed model APIs. So anyone launching an open model today or situationally
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Growing division between exponential and steady-state AI beliefs
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A thing I am noticing is the number of folks who believe AI is “real” is larger, but now there is a growing division between people who know that we are on an exponential & those whose mental model is that we are at a sort of steady state. The difference leads to misunderstanding
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Debate on open vs frontier model capability gap and switching difficulty
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That is probably right on where we disagree. I believe the capability delta outside of coding between open & frontier is much larger. I also am suspicious that open models will continue to stay at the frontier. I also think switching between models is harder for many tasks in
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Open weights models debate – request for persuasive project links
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I talk to lots of people in the open weights space, including some of the key players. I use open weights models, I think I just disagree with you (in part because I care a log about non-coding uses). Feel free to send a link to the project/idea that might persuade me otherwise
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Banning Chinese models will only boost their popularity
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Yes, and they will lose. What, are they going to ban all of China's models? That will just make them more popular:
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Open source importance vs closed frontier models lead
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I think open source is important (it was literally the subject of a bunch of my pre-AI academic research). I also think that closed frontier models have a current lead with sustaining forces for now. And that more intelligent models can do more. Not sure we disagree on that much.
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ByteDance’s iLLaDA 8B diffusion model rivals autoregressive LMs
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"Improved Large Language Diffusion Models" ByteDance just made bidirectional masked diffusion on-par with autoregessive LM! This paper iLLaDA trains an 8B Transformer from scratch on 12T tokens, then keeps the same denoising objective for SFT on a 25B-token instruction corpus.
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Deep vibe research: even crazier paths than vibe coding
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If you think that vibe coding can lead you down some crazy wrong paths, try deep vibe research!
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Sakana AI’s Fugu dynamically routes queries to multiple models
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Sakana Fugu Technical Report Instead of training one larger model, Sakana AI trains an orchestrator that reads each query and dynamically routes or composes GPT-5.5, Gemini-3.1-Pro, Claude Opus 4.8 and other agents into query-specific workflows. With Fugu being the fast router,