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Whitepapers

质子梯度研究白皮书

AtomGradient research whitepapers

我们围绕端侧持续学习发布研究白皮书：研究立场、已经建立的算法与工程基础，以及下一代 Neural Imprint 的演进方向。

Research whitepapers on on-device continual learning: our position, the algorithmic and engineering foundations we have established, and the direction of next-generation Neural Imprint.

最新发布

Latest

Neural Imprint · Whitepaper v2 · 中文 · 2026-09-17

NI 下一代：持续学习的愿景、哲学与技术路径

白皮书 v2 · 质子梯度（AtomGradient） · 2026 年 9 月 17 日

这份白皮书阐述质子梯度对持续学习的研究立场、已经建立的算法与工程基础，以及下一代 Neural Imprint 的演进方向。

  • NI = 持续学习算法与算法架构，以及围绕它构建的整套技术栈
  • 研究立场：设备就是智能体，智能走向数据
  • 已建立的机制：RPP、Directional Steering、DSR、FrogJump 与三项代表性实测
在线阅读 → PDF →
Neural Imprint · Whitepaper v2 · English · 2026-09-17

Next-Generation NI: A Vision, Philosophy, and Technical Path for Continual Learning

Whitepaper v2 · AtomGradient · September 17, 2026

This whitepaper presents AtomGradient's research position on continual learning, the algorithmic and engineering foundations we have established, and the direction of the next generation of Neural Imprint.

  • NI = a continual learning algorithm and architecture, plus the technology stack built around it
  • Research position: the device is the agent; intelligence goes to the data
  • Established mechanisms: RPP, Directional Steering, DSR, FrogJump, and three representative measurements
Read online → PDF →

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