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具身智能落地的最后20%,藏在「云」里

雷峰网 (AI科技评论) Embodied AI 2026-09-04

TL;DR - Real-world robot deployment increasingly depends on cloud infrastructure for remote operation, data pipelines, heterogeneous computing, and persistent agent runtimes. These capabilities address the difficult “last 20%” between controlled demonstrations and reliable operation at scale.

  • Cloud-edge-device coordination assigns complex training and perception to cloud GPUs while keeping latency-sensitive motion control on local NPUs or CPUs.
  • Remote operation requires secure, low-latency control and video transmission that remains usable under weak network conditions.
  • Large multimodal robotics datasets need scalable storage, streaming, governance, indexing, retrieval, and export into continuously running training pipelines.
  • Cloud agent runtimes can provide sandboxing, isolated data storage, long-term memory, and authorization so robots can safely execute user-defined skills over time.

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