静态网站悖论 个人网站的两种不同实现方式：一种是复杂的内容管理系统（CMS），另一种是简单的静态 HTML 文件。文章指出，尽管大多数普通用户倾向于使用复杂的解决方案（如 WordPress），但实际上，只有少数专业软件工程师能够选择更简单的静态网站。 via HackerNews 2024 10 09 前两天刚好听朋友说 square space 已经涨到了近乎搞笑的 $25 月费，做不用来盈利的个人博客实在难以 justify。这篇文章中吐槽得很在点子上： normal users are stuck with a bunch of greedy clowns that make them pay for every little thing, all while wasting ungodly amounts of computational power to render what could have been a static website in 99% of cases. 普通用户被困在了一群屁大点功能都要收费的贪婪小丑手里，与此同时浪费着人神共愤额度的算力来渲染 99% 的情况下都可以作为静态的网站。 当然原文中说的“只有少数专业软件工程师才能选择更简单的静态网站”略微夸张并不认同，因为静态站至少是比 self-host 的动态 CMS 少太多维护了。我的 backlog 里也一直躺了篇安利新手用静态站并拉踩 WP 的文，不过网上这种文已经有无数了也还是拦不住前赴后继往各种 CMS 的坑里冲的新手，觉得写了又有什么意义呢就还搁着没写。（当然迟早会像以前反复造的无数轮子一样被废话欲战胜的 but not today） #indieblog#newletter
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@repo_science · Post #4131 · 2024/05/18 21:06
#DL 📱 Zeus New Pytorch Ecosystem Tool Zeus is an open source toolkit for measuring and optimizing power consumption of deep learning workloads. 🖥Github ----- Main channel: @repo_science Coupons: @freecoupons_reposcience -----
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@amneumarkt · Post #706 · 2025/11/21 07:53
#dl Introducing more symmetries in attention https://github.com/NVIDIA/torch-harmonics https://neurips.cc/virtual/2025/loc/san-diego/poster/117783
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@amneumarkt · Post #691 · 2025/10/05 07:41
#dl Park, Chanwook, Sourav Saha, Jiachen Guo, Hantao Zhang, Xiaoyu Xie, Miguel A. Bessa, Dong Qian, et al. 2025. “Unifying Machine Learning and Interpolation Theory via Interpolating Neural Networks.” Nature Communications 16 (1): 1–12. https://www.nature.com/articles/s41467-025-63790-8
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@amneumarkt · Post #683 · 2025/06/28 07:04
#dl A few cool ideas in this model. Introducing Gemma 3n: The developer guide - Google Developers Blog https://developers.googleblog.com/en/introducing-gemma-3n-developer-guide/
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@amneumarkt · Post #681 · 2025/06/14 08:43
#dl So tensorflow and jax are deprecated in the transformers package. https://github.com/huggingface/transformers/pull/38758
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@amneumarkt · Post #662 · 2025/02/21 07:42
#dl Sure, nobody uses it anyways.
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@amneumarkt · Post #625 · 2024/10/03 21:31
#dl PyTorch Native Architecture Optimization: torchao | PyTorch https://pytorch.org/blog/pytorch-native-architecture-optimization/
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@amneumarkt · Post #624 · 2024/10/03 18:07
#dl https://soumith.ch/blog/2024-10-02-training-10k-scale.md.html
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@amneumarkt · Post #602 · 2024/07/20 05:48
#dl There is this new lib called scale. One could compile CUDA code to use it on AMD GPU. https://docs.scale-lang.com/manual/how-to-use/ I don't know who is more pissed off, NVidia or AMD.
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@amneumarkt · Post #556 · 2024/03/16 09:09
#dl This repo is really nice. yuanchenyang/smalldiffusion: Simple and readable code for training and sampling from diffusion models https://github.com/yuanchenyang/smalldiffusion
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@amneumarkt · Post #506 · 2023/11/13 08:30
#dl Google & USC benchmarked a prompt based forecasting method, and the results are amazing. Cao D, Jia F, Arik SO, Pfister T, Zheng Y, Ye W, et al. TEMPO: Prompt-based Generative Pre-trained Transformer for time series forecasting. arXiv [cs.LG]. 2023. Available: http://arxiv.org/abs/2310.04948
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@amneumarkt · Post #484 · 2023/06/12 06:13
#dl https://twitter.com/armin_kekic/status/1667181047480479751?s=20
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