我热爱大语言模型,我讨厌炒作。
I love LLMs, I hate hype

原始链接: https://geohot.github.io//blog/jekyll/update/2026/07/12/i-love-llms.html

作者作为一名资深人工智能专家和前黑客,对人工智能的飞速发展表达了极大的热情,并以本地模型和编程智能体作为证据,认为这标志着技术的实质性飞跃。他将人工智能视为计算机革命的自然延续——一种类似编译器或正则表达式的高效生产力工具,而非神秘莫测、改天换地的事件。 然而,作者严厉批评了围绕人工智能的“负面炒作”。他驳斥了关于“末日”情景或非得迁往旧金山发展的论调,称这些不过是制造焦虑的恐吓。此外,他指出各大前沿实验室通过将摩尔定律和开源创新带来的进步归功于己,以此人为抬高自身价值。作者认为,这些实验室恐惧技术被商品化,本质上是在保护各自的资金来源。 最终,作者拒绝接受极端的末日论,转而将人工智能视为一种实用且不断进化的技能组合。尽管他承认目前的“跟风式”人工智能内容多为“垃圾”,但他赞赏人工智能在提升编程效率方面的实际效用,并重申了他对计算机事业的热爱。

这篇 Hacker News 讨论帖探讨了大型语言模型(LLM)的真实效用与其行业炒作之间的矛盾。参与者普遍认为,虽然 LLM 是编码和个人生产力的强大工具,但从“错失恐惧症”(FOMO)到“奇点”预测等极端论调,更多是由企业营销和资本利益驱动的,而非基于技术现实。 主要观点包括: * **“个性化”时代:** 开发者正越来越多地利用 LLM 构建针对特定需求的“精简版”软件,但这可能给开源项目的维护带来风险,因为用户更倾向于快速分支,而非回馈上游代码。 * **炒作周期:** 参与者批评“AI”这一标签及引发焦虑的言论(如“永久底层阶级”论调)是操纵性手段,旨在推动资本投资并影响专业人才向旧金山等地聚集。 * **实用性与性能:** 用户将工具的实际价值(如作为“智能编译器”)与因缺乏专业指导而产生的“劣质内容”(slop)区分开来。 总之,大家的共识是:LLM 是一种强大的、非魔法的实用工具,而目前其真实面貌正被激烈的行业炒作所掩盖。
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原文

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!


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.

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.


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.


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. 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.

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