内容来源：https://aiweekly.co/issues/460

内容总结：

【2026：AI从“言”到“行”，万亿美元资本涌入实体层与智能体革命】

2026年被视为人工智能从“概念热潮”转向“实体行动”的关键分水岭。行业叙事已从“生成内容”激进地转向“自主执行”，资本正大规模流向芯片、能源、机器人等实体基础设施层，而软件则必须证明其能作为完全自主的“同事”参与工作。主题不再是“智能”，而是“行动”。

创投聚焦：垂直智能体与成本治理成热点
初创企业融资集中涌向“垂直智能体”（专精法律、人力资源、金融等场景）及管理其高昂运行成本的“FinOps”工具层。多智能体协作系统投资激增，实现风控、反欺诈等专业智能体协同完成复杂任务。行业报告显示，智能体正从“副驾驶”升级为执行端到端流程的自主“同事”。同时，无代码智能体开发平台兴起，催生“公民AI开发者”；治理即服务初创企业获风投青睐，专司监控与审计企业AI行为合规性。市场分析指出，投机性AI估值正集中于私募市场，基础模型融资规模呈现“主权级”分化。

技术演进：异构架构崛起，视频与推理模型成熟
“单一模型主导”时代终结。2026年异构架构成为主流：系统用巨型“推理模型”（如GPT-6）规划任务，而将执行交由高效小语言模型以控制成本。研究聚焦“系统2”式思考（先推理后输出）与智能体间自主通信协议。AI视频生成进入生产级，可生成长时间内容并保持角色一致性；推理优先模型通过多步规划减少幻觉；边缘侧个人智能体依托本地小模型保障隐私与实时性。此外，实时情感语音生成、按需生成界面等突破预计将重塑交互体验。

应用落地：“人机协作三明治”模式普及，渗透率跃升
应用核心转向“协作而非替代”。广泛采用的“三明治”工作模式为：人类制定策略、AI执行数据密集型任务、人类最终审核。高德纳预测，2026年底40%的企业应用将嵌入专用AI智能体（2025年不足5%），根本性重塑工作流。具体场景包括：医疗领域实现全流程就诊协调、工厂通过物联网数据预测故障并自主触发维护、科研智能体直接参与实验设计、代码库智能体实现架构级理解等。

市场趋势：2.5万亿美元基建投资遭遇供应链瓶颈
2026年AI市场叙事转向“基础设施现实”。全球AI支出预计达2.52万亿美元（同比增44%），但内存短缺危机可能推高硬件成本并导致PC市场收缩。边缘AI硬件市场将突破300亿美元，受智能手机与工业机器人本地化处理需求驱动。投资主题聚焦“经济安全”，资本流向支撑AI规模的弹性供应链与能源网络。亚太地区IT支出预计增至1.12万亿美元，正从“AI实验”转向由智能体驱动半数新经济价值的“自主未来”。市场整合加速，大型企业已占据近60%市场份额。

（完）

中文翻译：

2026：行动之年？

2026年标志着"炒作阶段"的结束和"实体阶段"的开始。行业叙事已从"AI能说什么"（生成式）急剧转向"AI能做什么"（智能体）。我们正见证资本大规模转向"实体层"——芯片、能源和机器人技术，而软件则被迫证明其能充当完全自主的"同事"。2026年的主题不是"智能"，而是"行动"。

初创动态
AI初创与融资：验证之年？
热钱正涌入"垂直领域智能体"（专精于法律、人力资源、金融）以及管理这些自主智能体激增成本所需的"财务运营"层。

• 多智能体系统兴起：对"多智能体系统"的投资激增，初创公司正在构建协调层，使专业智能体（如"风险智能体"和"欺诈智能体"）能在贷款审批等复杂任务上协作。
• 垂直智能体专业化：Forrester报告显示，趋势正转向"垂直智能体"，它们不仅在特定行业（如旅游、医疗）中对话，更能执行端到端流程，从"副驾驶"模式演进为完全自主的"同事"。
• 智能体的FinOps：新兴初创公司正着手解决"智能体成本优化"问题，提供工具来追踪和控制长期运行自主智能体的令牌使用，这正成为企业的关键痛点。
• 无代码智能体构建器：通过"无代码智能体"平台，AI民主化正在加速，使非技术背景的业务领导者也能配置工作流智能体，催生新的"公民AI开发者"群体。
• 治理即服务：风投正支持"治理智能体"初创公司，这些公司部署专用模型来监控、审计和规范其他企业AI智能体的行为，以确保合规。
• 转向私募资本：市场分析表明，投机性的AI估值正集中在私募市场，基础模型的"主权级"融资轮与应用层注重实用性的较小规模融资轮出现分化。

研究前沿
AI研究与创新
"单一模型统治一切"的时代已终结。2026年是异构架构之年，系统使用庞大的"推理模型"进行规划，但将执行任务卸载给高效的"小语言模型"以控制成本。研究高度聚焦于"系统2"思维（即模型暂停并进行推理）以及允许模型间无需人工干预即可通信的"智能体间协议"。

• 视频生成成熟化：到2026年，AI视频模型预计将达到生产级水平，能够生成长达数分钟、角色连贯且符合物理规律的内容，超越短视频片段，取代库存素材。
• 推理优先模型兴起：行业正转向"推理优先"模型，其优先考虑逻辑和多步骤规划而非速度，通过在输出答案前强制执行"思考"步骤来减少幻觉。
• 边缘优先的个人智能体：预测显示，个人智能体将向边缘迁移，由设备本地运行的强大"小语言模型"驱动，以确保隐私并降低延迟。
• 用于基准测试的智能体测试框架：AI实验室正超越静态基准测试，转向"智能体测试框架"——这是为测试模型能否可靠执行长达数日的工作流（而非仅回答问题）而设计的复杂环境。
• 音频模型突破：实时音频生成正成为"最被低估的突破"，2026年的模型能够进行即时、富有情感的声音交互，很可能淘汰传统的交互式语音应答系统。
• 生成式用户界面：研究预测"生成式用户界面"将在2026年兴起，应用程序根据用户意图动态生成定制界面，超越静态菜单，实现动态、情境感知的控件。

应用场景
AI研究与实际应用
2026年的应用场景核心是"协作，而非替代"。我们正广泛采用工作的"三明治模型"：人类制定战略，AI智能体处理数据密集型的执行工作，人类提供最终审批。

• 40%的企业渗透率：Gartner预测，到2026年底，40%的企业应用程序将嵌入特定任务AI智能体，较2025年的不足5%实现巨大飞跃，从根本上重塑工作流程。
• 工作的"三明治模型"：微软强调工作流正向协作模式转变：人类定义意图并审核结果，而AI处理执行过程中"混乱的中间环节"，使小团队能在数天内发起全球性活动。
• 科学发现智能体：微软研究院展望2026年将成为AI进入实验室之年，超越总结归纳，主动提出实验建议并助力物理、化学和生物学领域的发现。
• 医疗"护理协调"：对2026年的预测描述了"预约协调智能体"，它们能在无需行政人员介入的情况下，管理从检查保险资格到安排预约及后续跟进的全部患者旅程。
• 工厂车间智能：应用场景正扩展到工厂车间的"实体AI"，智能体利用物联网数据预测机器故障，并在停机发生前自主触发维护订单。
• 代码库智能：GitHub预测2026年"代码库智能"将兴起，AI不仅能理解代码语法，更能理解代码库的完整历史和关联，从而实现高级架构推理。

市场要闻
AI公开市场：2.5万亿美元基础设施资本支出，同比增长44%
2026年的市场叙事已从"炒作"转向"基础设施现实"。我们正进入一个由物理约束而非仅模型能力定义的"硬件超级周期"。主导主题是高达2.5万亿美元的资本支出预测，但这正与内存和能源领域的关键供给侧瓶颈发生碰撞。投资者大力奖赏那些掌控AI"实体层"（电力、内存、主权数据中心）的公司，同时惩罚那些无法证明能带来即时生产力提升的软件公司。

• 2.5万亿美元支出激增：Gartner预测，2026年全球AI支出将达到2.52万亿美元，同比增长44%，这巩固了AI作为新经济基础设施的地位。
• 内存危机影响：IDC警告2026年将出现"内存短缺危机"，DRAM和NAND供应滞后于需求，可能推高硬件成本并使PC市场收缩近5%。
• 边缘AI硬件繁荣：受智能手机和工业机器人转向本地处理以降低云端推理成本的推动，边缘AI硬件市场预计在2026年将达到307.4亿美元。
• 经济安全主题：高盛将"经济安全"确定为2026年的主导投资主题，资本将流入维持AI扩展所需的弹性供应链和能源电网。
• 亚太区加速：IDC预测，随着该地区从"AI实验"转向"智能体驱动的未来"（AI将驱动50%的新经济价值），2026年亚太区IT支出将增长7%，达到1.12万亿美元。
• 生成式AI市场估值：Fortune Business Insights估计2026年全球AI市场价值为3759.3亿美元，并指出随着整合加速，大型企业现已占据近60%的市场份额。

英文来源：

2026 the year of Action?
2026 marks the end of the "Hype Phase" and the start of the "Physical Phase." The narrative has shifted aggressively from what AI can say (Generative) to what AI can do (Agentic). We are witnessing a massive capital pivot toward the "Physical Layer"—chips, energy, and robotics—while software is being forced to prove it can act as a fully autonomous coworker. The theme for 2026 is not "Intelligence," it is "Action."
Startup News
AI Startups & Funding. : The year of the proof?
The hot capital is flowing into "Vertical Agents" (specialized for law, HR, finance) and the "FinOps" layer needed to manage the spiraling costs of these autonomous agents.

• Rise of Multi-Agent Systems (MAS): Investments are surging in "Multiagent Systems", where startups are building orchestration layers that allow specialized agents (e.g., a "Risk Agent" and a "Fraud Agent") to collaborate on complex tasks like loan underwriting.
• Vertical Agent Specialization: Forrester reports a shift toward "Vertical Agents" that don't just chat but execute end-to-end processes in sectors like travel and healthcare, moving beyond the "copilot" model to fully autonomous "coworkers."
• FinOps for Agents: New startups are emerging to address "Agent Cost Optimization", providing tools to track and control the token usage of long-running autonomous agents, which is becoming a critical enterprise pain point.
• No-Code Agent Builders: The democratization of AI is accelerating through "No-Code Agent" platforms, enabling non-technical business leaders to configure workflow agents, creating a new class of "Citizen AI Developers."
• Governance as a Service: VCs are backing "Governance Agent" startups, which deploy specialized models solely to monitor, audit, and police the behavior of other enterprise AI agents to ensure compliance.
• Shift to Private Capital: Market analysis indicates that speculative AI valuations are concentrating in private markets, with "sovereign-scale" rounds for foundation models bifurcating from smaller, utility-focused rounds for application layers.
  Research
  AI Research & Innovation (Models)
  The "One Model to Rule Them All" era is dead. 2026 is the year of Heterogeneous Architectures, where systems use massive "Reasoning Models" (like GPT-6 or Gemini 3) for planning, but offload execution to highly efficient "Small Language Models" (SLMs) to keep costs viable. Research is heavily focused on "System 2" thinking—models that pause and reason—and "Agent-to-Agent" (A2A) protocols that allow models to communicate without human intervention.
• Video Generation Maturity: By 2026, AI video models are expected to be production-grade, capable of generating minutes of content with consistent characters and physics, moving beyond short clips to replace stock footage.
• Rise of Reasoning-First Models: The industry is shifting toward "Reasoning-First" models that prioritize logic and multi-step planning over speed, reducing hallucinations by enforcing "thought" steps before outputting answers.
• Edge-First Personal Agents: Predictions indicate that personal agents will migrate to the edge, powered by capable Small Language Models (SLMs) running locally on devices to ensure privacy and reduce latency.
• Agent Harnesses for Benchmarking: AI Labs are moving beyond static benchmarks to "Agent Harnesses"—complex environments designed to test if models can reliably execute multi-day workstreams rather than just answer questions.
• Audio Model Breakthroughs: Real-time audio generation is becoming the "most underrated breakthrough", with 2026 models capable of instant, emotional voice interaction that will likely retire legacy IVR systems.
• Generative UI: Research predicts "Generative UI" will take off in 2026, where applications generate custom interfaces on-the-fly based on user intent, moving beyond static menus to dynamic, context-aware controls.
  Applied use cases
  AI Research & Applied Use Cases
  The applied use case for 2026 is "Collaboration, not Replacement." We are seeing the widespread adoption of the "Sandwich Model" of work: Humans set the strategy, AI agents handle the data-heavy execution, and humans provide the final sign-off.
• 40% Enterprise Penetration: Gartner predicts that 40% of enterprise applications will have embedded task-specific AI agents by the end of 2026, a massive leap from less than 5% in 2025, fundamentally reshaping workflows.
• The "Sandwich Model" of Work: Microsoft highlights a shift to a collaborative workflow where humans define intent and review results, while AI handles the "messy middle" of execution, allowing small teams to launch global campaigns in days.
• Scientific Discovery Agents: Microsoft Research envisions 2026 as the year AI joins the lab, moving beyond summarization to actively suggesting experiments and aiding discovery in physics, chemistry and biology.
• Healthcare "Care Orchestration": Forecasts for 2026 describe "Appointment Orchestration Agents" that manage the entire patient journey—from checking insurance eligibility to scheduling and follow-ups—without administrative staff involvement.
• Factory Floor Intelligence: Use cases are expanding into "Physical AI" on the factory floor, where agents use IoT data to predict machine failures and autonomously trigger maintenance orders before downtime occurs.
• Repository Intelligence: GitHub predicts the rise of "Repository Intelligence" in 2026, where AI understands not just code syntax but the entire history and relationship of a codebase, enabling high-level architectural reasoning.
  Market News
  AI Public Markets, massive 2.5 trillions earmarked for infra capex a 44% YoY increase
  The market narrative for 2026 has shifted from "hype" to "infrastructure reality." We are entering a "Hardware Supercycle" defined by physical constraints rather than just model capabilities. The dominant theme is the massive $2.5 trillion CapEx projection, but this is colliding with a critical supply-side bottleneck in memory and energy. Investors are heavily rewarding companies that secure the "physical layer" of AI—power, memory, and sovereign data centers—while punishing software firms that cannot demonstrate immediate productivity gains.
• $2.5 Trillion Spending Surge: Gartner forecasts worldwide AI spending will reach $2.52 trillion in 2026, a 44% year-over-year increase that cements AI as the new economic infrastructure.
• Memory Crisis Impact: IDC warns of a "Memory Shortage Crisis" in 2026, with DRAM and NAND supply lagging demand, likely driving up hardware costs and contracting the PC market by nearly 5%.
• Edge AI Hardware Boom: The Edge AI hardware market is projected to reach $30.74 billion in 2026, driven by a shift toward local processing on smartphones and industrial robots to reduce cloud inference costs.
• Economic Security Theme: Goldman Sachs identifies "Economic Security" as the dominant investment theme for 2026, with capital flowing into resilient supply chains and energy grids required to sustain AI scaling.
• Asia-Pacific Acceleration: IDC predicts that IT spending in Asia-Pacific will grow 7% to $1.12 trillion in 2026, as the region pivots from "AI experimentation" to an "Agentic Future" where AI drives 50% of new economic value.
• Generative AI Market Valuation: Fortune Business Insights values the global AI market at $375.93 billion in 2026, highlighting that large enterprises now hold nearly 60% of the market share as consolidation accelerates.