Self-learning AI encompasses systems capable of independently enhancing their performance over time by learning from data and experiences without explicit programming. A core enabling technology is reinforcement learning, a machine learning paradigm where an intelligent agent learns to make optimal decisions through trial and error. This process involves the agent taking actions within a dynamic environment and receiving feedback in the form of rewards or penalties, allowing it to develop strategies that maximize a cumulative reward signal. Primary applications for this technology are transforming numerous sectors, including industrial automation, autonomous navigation in vehicles, algorithmic trading in financial industries, personalized treatment strategies in healthcare, and sophisticated natural language processing.

Global predictive AI in stock market encompasses the application of advanced computational technologies, including machine learning, deep learning, and natural language processing, to analyze vast and complex financial datasets. This technology processes historical price data, corporate filings, macroeconomic indicators, and real time news sentiment to identify patterns and forecast future stock price movements, market trends, and volatility. The primary objective is to generate data driven, actionable insights that enhance algorithmic trading strategies, optimize portfolio management, and improve risk assessment frameworks. This market represents a significant shift from traditional technical and fundamental analysis toward more sophisticated, automated, and probabilistic models for investment decision making.

Predictive AI in retail market refers to the application of advanced analytical technologies, including machine learning, statistical algorithms, and data mining, to analyse historical and real time data. The primary objective is to forecast future events, consumer behaviours, and market trends with a high degree of accuracy. This technology enables retail organizations to transition from a reactive to a proactive operational stance by anticipating outcomes related to sales, inventory requirements, and customer preferences. By processing vast datasets that encompass transaction histories, customer interactions, and external market factors, predictive AI provides actionable insights. These insights empower retailers to make informed, data driven decisions across various functions such as merchandising, supply chain management, marketing, and customer service, ultimately aiming to enhance operational efficiency, minimize risks like overstocking or stockouts, and personalize the customer journey to foster loyalty and drive revenue growth.

The market by value in this report is defined as the revenues that enterprises gain from goods and/or services sold within the specified market and geography. • Values in this market are ‘factory gate’ values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market by value in this report is defined as the revenues that enterprises gain from goods and/or services sold within the specified market and geography. • Values in this market are ‘factory gate’ values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

2025 年 12 月 18 日，火山引擎在 2025 冬季 FORCE 原动力大会上发布了面向多模态 Agent 场景优化的豆包大模型在 2025 FORCE 原动力大会开发者日（上海）上，火山引擎围绕智能体（Agent）规模化生产与应用落地的关键路径，对其开发者生态进行了系统化升级与集中发布。具体而言，在大模型服务平台火山方舟方面，公司推出新一代 Responses API、上线 Serverless RL（强化学习）平台，并增强了 VikingDB 向量数据库及 Viking 记忆库的功能；面向企业级应用，发布并升级了 AgentKit 企业级 AI Agent 平台底座能力，同时在开发工具侧推出扣子编程与 TRAE CN 企 业版。此外，公司亦将原有开发者社区升级为专注 Agent 的开发者社区，并同步上线动手实验室、核心开发者计划及城市社区等系列生态支持举措。

2025 年 12 月 18 日，火山引擎在 2025 冬季 FORCE 原动力大会上发布了面向多模态 Agent 场景优化的豆包大模型 1.8 及音视频创作模型 Seedance 1.5 Pro，并同步更新了企业 Agent 落地支持体系与阶梯式成本方案。截至 12 月，豆包日均 token 使用量突破 50 万亿，同比增长超 10 倍，服务超百家万亿级企业客户，表明模型已在生产环境中实现规模化验证。Seedance 1.5 Pro 通过原生音视频联合生成架构实现毫秒级音画同步与多语言口型适配，其“Draft 样片”机制可提升约 65%创作效率。企业端，火山引擎推出 AgentKit/HiAgent 平台及“AI 节省计划”，以平台化工具与用量阶梯折扣推动 Agent 从试点走向规模化部署，构建“模型-平台-定价”一体化的竞争壁垒。

The global AI-ready cloud solutions market encompasses a specialized segment of the cloud computing industry, providing infrastructure, platforms, and services explicitly designed to support and scale artificial intelligence and machine learning workloads. These solutions are characterized by their high-performance computing capabilities, including access to specialized processors like GPUs and TPUs, and scalable storage and networking to handle massive datasets. AI-ready cloud solutions also feature integrated AI and machine learning frameworks, MLOps platforms for automating the machine learning lifecycle, and APIs for seamless integration of AI capabilities into existing applications. This market caters to the increasing demand from enterprises for agile, cost-effective, and powerful environments to develop, deploy, and manage AI-driven applications, thereby enabling innovations such as predictive analytics, natural language processing, and intelligent automation without the need for substantial upfront infrastructure investments.

The global AI-powered radio access network market encompasses the integration of artificial intelligence and machine learning technologies within the cellular network infrastructure that connects end user devices to the core network. This technology functions by employing sophisticated algorithms to continuously analyze real time network data, enabling the autonomous optimization of RAN operations. Key applications include predictive analytics for network maintenance, intelligent traffic steering, dynamic energy consumption management, and automated resource allocation for 5G network slicing.

The global agentic AI for financial services market encompasses intelligent systems and platforms capable of autonomous action to achieve complex, predefined objectives within the financial industry.