请问HN：更智能的AI模型是如何制作的？
我很好奇两代人工智能模型之间究竟发生了什么。<p>例如，如何从Sonnet发展到Opus？Opus是从头开始训练的，还是基于Sonnet构建的，或者是与Sonnet大致相同但计算能力和训练量更大的模型？<p>像Astra这样的模型为何能在某些能力上突然实现大幅跃升？是什么阻止了Anthropic、Mistral或其他公司做同样的事情？<p>主要的区别仅仅是更多的计算能力和资金，还是有训练方法、数据、架构和研究突破是竞争对手可能不知道的？<p>我想不出更合适的地方来询问这个问题。我猜这里有一些人实际上在这些模型上工作，并知道背后的情况。
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I am curious what actually happens between two generations of AI models.<p>For example, how do you go from Sonnet to Opus? Is Opus trained from scratch, built on Sonnet, or mostly the same model with more compute and training?<p>And how do models like Astra suddenly make a big jump in some capabilities? What is stopping Anthropic, Mistral, or others from doing the same thing?
Is the main difference just more compute and money, or are there training methods, data, architecture, and research breakthroughs that competitors may not know about?<p>I can't think of a better place to ask this. I am guessing there are people here who actually work on these models and know what goes on behind the scenes.