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more on this when you launch a cuda kernel, you are not running a function per say like we do in c++, you are handing an abstract specification of a parallelism, often in an intermediate form called ptx, to the nvidia driver, the driver acts as a final stage, just in time…
more on this when you launch a cuda kernel, you are not running a function per say like we do in c++, you are handing an abstract specification of a parallelism, often in an intermediate form called ptx, to the nvidia driver, the driver acts as a final stage, just in time…
Efficient training of neural networks is difficult. Our second Connectionism post introduces Modular Manifolds, a theoretical step toward more stable and performant training by co-designing neural net optimizers with manifold constraints on weight matrices.…
RL research is becoming like pretraining/modeling. This is a huge vibe shift. Most research published on RL isn't using enough compute to make many of these decisions matter as much. This is slowly shifting.
RL research is becoming like pretraining/modeling. This is a huge vibe shift. Most research published on RL isn't using enough compute to make many of these decisions matter as much. This is slowly shifting.
Evaluating reasoning models is non-trivial. But you can use a verifier to check if answers are indeed correct. Just finished a 35-page chapter on building one from scratch. Lots of symbolic parsing, math equivalence, edge cases… quite the project. Sneak peek on GitHub below 🔗
If you want to learn more about current LLM training recipes two of the best resources I've found that contain the juicy details (and not just evals): 1. Nemotron-H paper by Nvidia 2. SmolLM3 post by Hugging Face
If you want to learn more about current LLM training recipes two of the best resources I've found that contain the juicy details (and not just evals): 1. Nemotron-H paper by Nvidia 2. SmolLM3 post by Hugging Face https://t.co/nGVWNrgrvw
You can now train OpenAI gpt-oss with Reinforcement Learning in our free notebook! This notebook automatically creates faster kernels via RL. Unsloth RL achieves the fastest inference & lowest VRAM vs. any setup - 0 accuracy loss gpt-oss-20b GRPO Colab: colab.research.google.com/github/unsloth…
发现一家很不错的vps厂商 Voyracloud,除了普通的vps,还提供海外住宅ip服务器 我买了一个拿来用claude code和运营reddit,用的北美ip,里面是windows系统,搭配指纹浏览器直接直连用,目前用了两天很稳 现在用优惠码 4RMZISQY…
费曼说过 "真相,往往比你想象的要简单!" DeepMind 推理团队创始人 Denny Zhou 在斯坦福大学 CS25 课程上的一次分享,深刻透析了大语言模型推理的本质👀 LLMs 只是概率模型,它们不是人类!推理能力早已蕴藏在预训练模型中,我们缺少的不是能力本身,而是发现它的正确解码策略🤔 Rich Sutton…
(1/6) triton kernels are a great way to understand ML models. but tutorials are scattered the learning method for me was jst to read real, high performance code so i wrote a blog which walkthroughs the design and intuitions behind FLA's softmax attention kernel 🧵also a thread
我再也不用刷到深夜找热点。 把 Trend Finder 挂上,AI 秒扫 200+ 大 V 推文和官网更新,真正起风就 Slack 喊我。节省 3 小时,灵感先人一步。 github.com/ericciarla/tre…
看到了个 HuggingFace 的从0预训练大模型的框架——picotron (擎天棍?哈哈哈) 这个库更注重于教学,核心部分的文件,每个代码都不到300行。(这里还是来个小技巧,看不懂源代码可以塞给AI让AI给你讲是干什么的。见图2)另外官方还给了视频教程,可以说是十分贴心了。…
找到了个巨猛的 CUDA 教程。7K Star, 特别适合新手看。教程也是国人写的哦,有中文。并且更新也很快,像刚出的 HunyuanImage-2.1 相关内容也有。 地址:github.com/xlite-dev/Leet…
Comparing & Contrasting Recent LLMs Architecture > DeepSeek-V3/R1 > OLMo 2 > Gemma 3 > Mistral Small 3.1 > Llama 4 > Qwen3 (dense+MoE) > SmolLM3 > Kimi 2 > GPT-OSS Are 2025 LLMs really that different from each other? MoE, MLA, GQA, sliding window, normalization games & more.
三个小时的播客听完了,太好了! 2023年读到ReAct,被这篇paper正面影响了学术轨迹和工作内容,并开始关注 Shunyu 的工作, ReAct, SWE agent, r-bench 每篇都是过一段时间就拿出来读一下,Shunyu是我最喜欢的 Agent 研究员。…
三个小时的播客听完了,太好了! 2023年读到ReAct,被这篇paper正面影响了学术轨迹和工作内容,并开始关注 Shunyu 的工作, ReAct, SWE agent, r-bench 每篇都是过一段时间就拿出来读一下,Shunyu是我最喜欢的 Agent 研究员。… https://t.co/marTxTzSHH
When I started LLMs-from-scratch I just hoped it might help a few people learn. Just saw the GitHub the repo has now been forked 10k times! More than the stars, the best part is seeing thousands of people actually use and build on the code ☺️
Understanding GPU Architecture from Cornell cvw.cac.cornell.edu/gpu-architectu… During a low-level discussion at a casual meetup, many folks were interested in understanding GPUs more closely. While CPUs optimize for complex control flow (see those big cores + caches), the GPUs maximize…
This is a new 100-page RL for LLM literature review. It appears fairly complete. It also covers static/dynamic data and frameworks. And it has some nice figures! 🔗arxiv.org/abs/2509.08827

Ryan Chan @ryanchankh
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854 Followers 7K Following I am Subroto Palit, a professional T-shirt designer with 2+ years of experience in the Print-on-Demand (POD) industry.
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136K Followers 1K Following Prompt Engineer, dedicated to learning and disseminating knowledge about AI, software engineering, and engineering management.
めんま「追悼ア... @TianqiChen666
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Anne阿伦 @anne_lyl
2K Followers 251 Following 这里用中文记录 @anne_lyl Here try getting used to Engligh content more @anneincoding 16666
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Noam Brown @polynoamial
92K Followers 856 Following Researching reasoning @OpenAI | Co-created Libratus/Pluribus superhuman poker AIs, CICERO Diplomacy AI, and OpenAI o3 / o1 / 🍓 reasoning models
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2K Followers 1K Following Dropped out of tech. Invented the wheel instead.
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Zeyuan Allen-Zhu, Sc.... @ZeyuanAllenZhu
21K Followers 465 Following physics of language models @ Meta (FAIR, not GenAI, not TBD) 🎓:Tsinghua Physics — MIT CSAIL — Princeton/IAS 🏅:IOI x 2 — ACM-ICPC — USACO — Codejam — math MCM
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27K Followers 2K Following 有个很可爱的人,正在读我的简介/infp/脾气超好,不会炸毛/如果喜欢我,可以考虑投喂肉肉 https://t.co/LCtq8a8PkK
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Pengjie Ren @jayren3
380 Followers 302 Following Professor at Shandong University working on NLP and IR.
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