And all the evidence is is that is that models are getting better all this other stuff at the same time as they are improving in coding. More recent models are more creative, for example. Still plenty of jaggedness, but the frontier moves more in synch than we might expect
@emollick
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AI impresses non-coders too, selection bias on X
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There are plenty of people who are awed by AI who are not coders, I think the argument that AI impresses programmers most is, in part, selection bias on X, which is heavy on coders and people making fun of non-coders for not getting AI.
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AI is jagged but also surprisingly general across domains
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AI is jagged, but I think sometimes it is easy to overly focus on that. The generalness is a surprise too! LLMs may be optimized for verifiable fields like coding, but AI is also not bad at corporate strategy & medical advice & writing a sestina & expressing empathy & ideation.
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AI enables fun e-ink weather display with nano banana and rotating styles
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One fun thing about AI is that it lets you play with interfaces and approaches to displaying information in new ways without a lot of effort. I got a an internet connected e-ink display and set it up to show me the weather as interpreted by nano banana using rotating styles.
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Small model makers increase but performance gap with large models persists
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There are more competitive small model makers, but there is still a very big gap between what small models can do and what large models can accomplish (even if the small model benchmarks say otherwise)
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US labs abandon open weights, Chinese labs key
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The US frontier labs have all walked away from open weights. They continue to occasionally release excellent open models (Gemma 4, etc), but they are smaller models that are not competitive with their closed weights models. So all eyes are on Chinese AI labs for open models.
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Open questions about RSI, LLM gains, Chinese models, and open weights
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Lots of open questions: is RSI indeed happening at the Big Three labs? How long can the exponential of LLM ability gain last? How much do Chinese models rely on distillation, and can they keep pace given chip constraints? Will there continue to be frontier open weights models?
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Frontier AI models: US closed-source leaders, xAI falls behind
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So we now have a pretty good picture of the state of the frontier AI model makers. US closed source models continue to lead. Google, OpenAI, and Anthropic stand well ahead of the pack, and may have signs of recursive self-improvement. xAI has fallen from frontier status for now
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Amazon Nova 2 trails Sonnet 4.5 and remains in preview
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So what's the deal with Amazon Nova? They released Nova 2 in December, and even then, the top flight Nova 2 model trailed Sonnet 4.5. And it still hasn't left preview.
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Chatbot needs thinking trace and code visibility; web searches shallow, hallucination defensiveness
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For the chatbot? Can't do much that is valuable without some sort of thinking trace or ability to see code it writes. Web searches are very shallow and then the model tends to just throw back the answers it finds as gospel. Also a lot of defensiveness around its hallucinations.