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39:17
杨植麟演讲文字版重点和总结随着AI进入深度发展阶段，模型竞争的重点正在发生变化。未来的核心不再只是参数规模的堆叠，而是围绕效率、架构和应用能力展开全面竞争第一：效率革命：更少Token，更强智能传统大模型依赖大量计算资源，而新一代AI更关注Token使用效率。通过优化训练方式和推理机制，模型能够以更低成本完成更复杂的任务。这意味着未来AI商业化落地的关键，不只是拥有更大的模型，而是如何让模型运行得更快、更便宜、更稳定第二：架构革命：Linear Attention打破长文本瓶颈Kimi探索的新型Attention架构，进一步提升了长上下文处理能力。相比传统Transformer，Linear Attention 可以降低计算压力，让 AI 在处理超长文本、复杂知识库以及企业级任务时更加高效。这为未来 AI Agent 执行复杂任务提供了基础设施第三：应用革命：Agent Swarm推动AI自动化未来AI不再只是回答问题，而是成为能够自主规划和执行任务的智能体。多个Agent可以分工协作，完成研究、分析、代码开发、商业决策等复杂工作。同时，多模态能力的发展也让 AI 能够理解文字、图片、
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