AlexZ 🦀
28.8K posts

AlexZ 🦀
@blackanger
System in Rust, Application in AI. Slow down. Have fun. Live well. INTJ-A. No ism. Lifelong Programmer and Writer. Study in Public, Building in Public. 🦀 保命

🚨 眾議院議長約翰遜(Speaker Johnson)的這番話簡直太精彩、太到位了: “馬克思主義、共產主義、社會主義……歸根結底,它們通往死亡!” “這一切始於一個前提:即不存在上帝。” 「如果沒有上帝,那就意味著你沒有任何與生俱來的個人尊嚴、自由或價值。你不過是另一種群居動物,僅僅是群體中的一員罷了!” “你知道群居動物和群體會遭遇什麼嗎?它們必須受到指引、控制和圈養。” 「當權者或許會提供一點保障,給些免費的施捨,但他們肯定會剝奪人們的自由。而最終,這一切通向死亡。” 「我看著那些學生,發現他們聽得目瞪口呆。我對他們說:『讓我告訴你們一件事,這種社會主義思想其實源自於馬克思主義。僅在20世紀,馬克思主義就導致了數千萬無辜生命的喪生!』」 「這是一條通往死亡的道路。我要告訴你們,它是錯誤的,因為它建立在一個錯誤的前提之上。如果拋棄了美國的立國理想與信條,你就不可能捍衛自己的自由。” @SpeakerJohnson

the "rewrite it in rust" meme should be "rewrite it in go" like 95% of the time the remaining 5% are for projects like: - the linux kernel - sqlite - chromium



I wasn't expecting that Go vs Rust tweet to hit a nerve. Quick elaboration based on what I've actually seen.
I build a distributed sandbox system that has both Go and Rust components. I have effectively unlimited access to the strongest models, so I've spent a stupid amount of time reviewing and cleaning up LLM-generated code in both languages.
The difference in reviewability is stark.
Go was designed for thousands of engineers at Google to collaborate without stepping on each other. It has very few concepts, so the code ends up looking similar no matter who (or what) wrote it. You see the same patterns everywhere. The err returns are verbose, but at least they're predictable. Channels are about as fancy as it gets. GC removes an entire class of mental overhead. Goroutines + mutexes just work for most concurrency needs.
As a result, LLM-written Go usually reads like a novel. You can understand what’s going on quickly.
Rust is the opposite. More power, more ways to do the same thing, more concepts you have to hold in your head. When an LLM writes it, you often can't tell if something is elegantly minimal or just over-engineered. Arc


WAIC 现场,排队时听到有两个外国人在聊入口处那个 Party members on duty 是什么意思🤣 (听着感觉说不定真的会有人以为这是什么 after party 之类的活动

Automatic harness evolution appears to be a promising path toward AI self-improvement, but we find that its gains still largely come from repeated sampling and show limited generalization. Blog post: yikee.github.io/harnessevoluti… Code: github.com/rethinking-har…


当你觉得所有场景都会被大模型替代的时候。 想一想小天才儿童手表。 想一想倾听者儿童播放器 想一想希沃的学习机 明明功能已经被手机和平板吊打,为什么还这么畅销? Ai 时代也一样,虽然大模型完全可以做到,但是还是会有垂直行业的垂直产品。






