I love LLMs, I hate hype

我热爱大语言模型，但我讨厌炒作

I think from this blog you may misunderestimate how absolutely giddy I am about AI. I did hacking from 2007-2014, after that my whole career has been devoted to AI. I love the progress. I’m so excited for the new LLMs, self driving cars, video generation models, and coding agents. I set up a Linux box with opencode on my local GLM-5.2 last week and wow like just saying install tmux with the geohot configuration works; the Year of the Linux Desktop is finally here!

从这个博客来看，你可能低估了我对人工智能的狂热程度。我在 2007 年到 2014 年间从事黑客技术研究，此后我的整个职业生涯都致力于 AI。我热爱这种进步。我对新的大语言模型（LLM）、自动驾驶汽车、视频生成模型和编程智能体感到非常兴奋。上周，我在本地的 GLM-5.2 上配置了一台运行开源代码的 Linux 机器，哇，仅仅是输入“安装带有 geohot 配置的 tmux”就能成功运行；“Linux 桌面之年”终于到来了！

What I don’t like is two things. One, this constant bullshit about some window closing, or the perpetual underclass, or falling hopelessly behind. This is negative valence hype, not only is it not true, it’s mostly designed to make you feel bad about yourself and move to shitty San Francisco where everything really does suck like how these people claim.

我不喜欢的是两件事。第一，那些关于“机会窗口正在关闭”、“永久底层阶级”或“无可救药地落后”的陈词滥调。这是一种负面的炒作，不仅不是事实，而且主要是为了让你感到自我怀疑，从而搬到那个糟糕的旧金山——那里确实像这些人所说的那样烂透了。

And two, this strawman jump from, oh hey, it’s a fancy autocomplete, smart compiler, better search engine, to it’s gonna like own the whole light cone bro like if you aren’t in SF and at the right parties there’s gonna be like a flash of light in the sky one day and you’re not even gonna know what happened but everything just Changed. I’ll bet you everything I have that this doesn’t happen. The people perpetuating this are terrible people, but the justice is that this is how they feel inside all the time themselves.

第二，这种稻草人式的逻辑跳跃：从“嘿，这只是个高级自动补全、智能编译器或更好的搜索引擎”，直接跳跃到“兄弟，它将统治整个光锥，如果你不在旧金山参加那些高端派对，某天天空会闪过一道光，你甚至不知道发生了什么，但一切都变了”。我敢拿我所有的一切打赌，这种情况不会发生。散布这种言论的人很糟糕，但讽刺的是，这正是他们内心深处时刻感受到的恐惧。

Here’s a cool presentation from 2016 about superintelligence. Here’s a movie from 1991 about machines taking over the world. A certain cult likes to claim credit for things that are happening with or without them, and this is my main argument against the valuation of frontier labs. It’s not that AI won’t create that much value, it’s that they won’t capture it. They try to dress it up with some high minded safety or China bullshit, but the core of the anti open source arguments is a fear of commodification. AI is something that’s happening mostly due to Moore’s law and general progress in computing, not something that they are doing. Of course they have a strong incentive against you finding this out, because then you might not want to give them billions of dollars.

这里有一个 2016 年关于“超级智能”的精彩演讲，还有一部 1991 年关于机器接管世界的电影。某个特定的“邪教”团体喜欢把无论有没有他们都会发生的事情归功于自己，这就是我反对前沿实验室高估值的主要论点。并不是说 AI 创造不了那么多价值，而是他们无法独占这些价值。他们试图用高尚的“安全”或“中国威胁论”来包装自己，但反对开源论调的核心是对“商品化”的恐惧。AI 的发展主要归功于摩尔定律和计算领域的整体进步，而不是他们个人的功劳。当然，他们有强烈的动机不让你发现这一点，否则你可能就不会愿意给他们投几十亿美元了。

I might have been a little harsh in The Eternal Sloptember about models not being able to program. What’s really happening is that programming is changing. Can compilers program? Here’s a Linus Torvalds quote about how agents make programming 10x more productive, but compilers make programming 1000x more productive. I think 10x and 1000x are extreme estimates, but I’m now pretty confident I’m getting better at using them and get some boost from the models. It is a new skill, and it’s not like I haven’t constantly been trying them.

我在《永恒的垃圾九月》（The Eternal Sloptember）中关于模型无法编程的评价可能有点苛刻。真正发生的是编程本身正在改变。编译器能编程吗？Linus Torvalds 曾说过，智能体能让编程效率提高 10 倍，但编译器能让编程效率提高 1000 倍。我认为 10 倍和 1000 倍是极端的估计，但我现在很有信心，我正在变得更擅长使用它们，并从模型中获得了一些提升。这是一项新技能，而且我一直在不断尝试它们。

You have to be really careful, they can increase cognitive fatigue, and all the vibe coded stuff is still slop (where’s all this new magical software that the productivity improvements should imply?). But models are useful just like find replace, stack overflow, or all the regexes I never learned how to write and now never will! AI is the continuation of the computer revolution. I love computers so much.

你必须非常小心，它们会增加认知疲劳，而且所有那些“凭感觉写出来的代码”仍然是垃圾（生产力提升所带来的那些神奇的新软件都在哪儿呢？）。但模型确实有用，就像“查找替换”、Stack Overflow，或者那些我从未学会、以后也永远不会去写的正则表达式一样！AI 是计算机革命的延续。我太爱计算机了。