沙利文发布《全球及中国端侧智能行业市场研究报告》
Frost & Sullivan Releases the " Global and China Edge Intelligence Industry Market Research Report"
端侧智能是AI与物理世界交汇的"最后一公里"，其产业化瓶颈不在算力规模的堆叠，而在"知识密度"的系统性提升。当前端侧智能（Physical AI）正处于从概念验证向规模化落地演进的关键节点。未来3至5年，将是端侧智能产业爆发的黄金窗口期，"知识密度"将成为衡量端侧AI竞争力的核心标尺。端侧大模型不仅是技术产品，更是国家、产业与个人在数字化时代的战略性资产。本报告将对比"规模法则"（Scaling Law）与公司提出的"密度定理（Density Theorem）的技术路径与商业逻辑，论证端侧AI为何必须选择后者。云端"规模法则"遭遇算力成本与数据隐私双重瓶颈，端侧"密度定理"（单位算力效能最大化）成为产业化破局的核心抓手。投资端侧智能，本质是投资"高知识密度基座模型 + 软硬协同"的综合能力，这是抢占未来"AI主权"制高点的战略入口。
云侧大模型的商业规模化进程，已清晰揭示出一条核心规律：模型能力的市场渗透并非呈线性演进，而是在突破某一临界点后，实现商业价值的跃迁式爆发——这一爆发节点无需等待完整AGI的落地，仅需模型能力跨越“足够实用”的核心阈值。端侧智能的发展将复刻这一逻辑：随着知识密度的系统性提升与积淀，端侧模型能力终将突破商业化临界点，进而触发规模化场景落地的爆发式增长；从更长远的发展维度来看，知识密度的持续深化，将最终推动端侧AGI的实现，届时所释放的产业价值，将远超当前行业认知与想象。
在这一进程中，率先突破知识密度临界点的企业，将优先捕获端侧智能商业化爆发的红利；而率先实现端侧AGI落地的企业，将主导并定义下一个时代的AI产业格局。
Edge intelligence represents the "final frontier" where artificial intelligence converges with the physical world. The bottleneck hindering its industrial-scale adoption is not merely the aggregation of computing power, but the systematic enhancement of "knowledge density." As Physical AI transitions from proof-of-concept to scaled deployment, the next three to five years will constitute a critical window for market explosion. In this context, knowledge density will emerge as the definitive benchmark for competitive advantage. Far more than mere technological artifacts, edge foundation models represent strategic assets for nations, industries, and individuals in the digital era.
This report contrasts the prevailing cloud-centric "Scaling Law" with our proposed "Density Theorem," examining their respective technical pathways and business logic to demonstrate why the latter is indispensable for edge AI. While the Scaling Law faces dual constraints of prohibitive compute costs and data privacy concerns, the Density Theorem—focused on maximizing performance per unit of compute—provides the key to industrial viability. Investing in edge intelligence is fundamentally an investment in the integrated capability of "high-knowledge-density foundation models plus software-hardware co-design." This integration serves as the strategic gateway to securing "AI sovereignty."
The commercialization trajectory of cloud-based large models has revealed a clear pattern: market penetration does not follow linear growth but experiences a step-function increase upon surpassing a critical threshold of utility—well before the arrival of full AGI. Edge intelligence is poised to replicate this dynamic. As knowledge density accumulates systematically, model capabilities will inevitably cross the threshold of commercial viability, triggering exponential growth in scenario-based deployments. Looking further ahead, the continuous deepening of knowledge density will ultimately pave the way for edge AGI, unlocking industrial value that vastly exceeds current industry projections.
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如果您对全球及中国端侧智能行业有进一步的研究需求，请联系我们：
沙利文 陆先生
E-mail: gabriel.lu@frostchina.com
