God of Prompt(@godofprompt)

Kimi founder and XLNet co-creator, Zhilin Yang: "Adam was invented in 2014, and now we have Muon Clip as a drop-in replacement. Attention was invented over eight years ago, and now we have Kimi Linear. Residual connections are now also challenged with attention residue." Three foundations of modern deep learning, all being replaced in the same generation of models. 39 minutes of pure insight from the architect behind Kimi, one of the most watched open models on earth right now. His team scaled Muon to o

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Kimi founder and XLNet co-creator, Zhilin Yang: "Adam was invented in 2014, and now we have Muon Clip as a drop-in replacement. Attention was invented over eight years ago, and now we have Kimi Linear. Residual connections are now also challenged with attention residue." Three foundations of modern deep learning, all being replaced in the same generation of models. 39 minutes of pure insight from the architect behind Kimi, one of the most watched open models on earth right now. His team scaled Muon to o

TL;DR · AI 摘要

Kimi模型团队在GTC keynote中展示了万亿参数模型、线性注意力机制和注意力残差技术，显著提升效率和性能。

核心要点

  • Kimi Linear线性注意力机制全面超越传统注意力机制
  • Muon模型达到1万亿参数规模，创历史新高
  • 注意力残差技术带来24%的token效率提升

结构提纲

按章节快速跳转。

  1. §技术革新背景

    现代深度学习三大基础正在被新一代模型技术取代。

  2. ·核心机制突破

    Kimi团队开发了线性注意力机制和注意力残差技术。

  3. ›规模突破

    Muon模型参数量达到1万亿，刷新行业纪录。

  4. ·效率提升

    注意力残差技术实现24%的token效率增益。

思维导图

用一张图看清主题之间的关系。

查看大纲文本（无障碍 / 无 JS 友好）
  • Kimi模型技术突破
    • 核心机制革新
      • 线性注意力机制（Kimi Linear）
      • 注意力残差技术
    • 规模突破
      • Muon模型1万亿参数
    • 效率提升
      • 24% token效率增益

金句 / Highlights

值得收藏与分享的关键句。

#深度学习#模型优化#Kimi#注意力机制
打开原文

Alex Prompter on X: "Kimi founder and XLNet co-creator, Zhilin Yang: "Adam was invented in 2014, and now we have Muon Clip as a drop-in replacement. Attention was invented over eight years ago, and now we have Kimi Linear. Residual connections are now also challenged with attention residue." Three https://t.co/yzQm7ZpLjz" / X

Alex Prompter

@alex_prompter

Kimi founder and XLNet co-creator, Zhilin Yang: "Adam was invented in 2014, and now we have Muon Clip as a drop-in replacement. Attention was invented over eight years ago, and now we have Kimi Linear. Residual connections are now also challenged with attention residue." Three foundations of modern deep learning, all being replaced in the same generation of models. 39 minutes of pure insight from the architect behind Kimi, one of the most watched open models on earth right now. His team scaled Muon to one trillion parameters (a first), built the first linear attention that outperforms full attention across the board, and introduced attention residue for a 24% token efficiency gain. Watch the full GTC keynote, then read all about Kimi below.

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