8月2 0日晚，百度发布了2 0 2 5年第二季度财报，总营收3 2 7亿元，核心净利润同比增长3 5%至 7 4亿元，但其中一组数字极具里程碑意义：AI新业务收入首次突破1 0 0亿元，同比增长3 4%。 百亿收入并非偶然的业绩爆发，而是技术积累与产品的落地，更是一家公司在AI长跑中从布 局到收获的完整叙事，是深耕AI领域十余年的收成兑现。 而百度之所以能成为这场行业爆发中的"先行者"，关键在于其长达十余年的提前布局——早 在2 0 1 3年，百度就启动了自动驾驶技术研发；2 0 1 7年，Ap o ll o平台正式对外开放；2 0 2 1年， 萝卜快跑开始商业化试点。这种"长期主义"的投入，让百度在技术积累、数据沉淀、场景适 配等方面形成了难以逾越的壁垒，当行业风口来临时，能最先收获红利。 花旗银行在研报中明确指出，百度与Ub e r、Ly ft的合作，对萝卜快跑进一步开拓具备商业化 潜力的全新市场具有积极意义，彰显了其在自动驾驶价值链中的核心能力。高盛也预测，随 着萝卜快跑规模的进一步扩大和盈利能力的释放，市场将重新评估这一业务的价值。毕竟， 在 全 球 范 围 内 ， 能 实 现 千 万 级 出 行 ...

Core Viewpoint - The article discusses the advancements in large models, particularly focusing on the performance of Baidu's Wenxin models, which have achieved high ratings in recent evaluations, indicating their strong capabilities in reasoning and multimodal integration [1][2]. Group 1: Model Performance and Evaluation - The China Academy of Information and Communications Technology (CAICT) recently evaluated large model reasoning capabilities, with Wenxin X1 Turbo achieving the highest rating of "4+" in 24 assessment categories [1]. - Wenxin X1 Turbo scored 16 items at 5 points, 7 items at 4 points, and 1 item at 3 points, making it the only large model in China to pass this evaluation [1]. Group 2: Technological Innovations - Wenxin models emphasize two key areas: multimodal integration and deep reasoning, with the introduction of technologies such as multimodal mixed training and self-feedback enhancement [6][11]. - The multimodal mixed training approach unifies text, image, and video modalities, improving training efficiency by nearly 2 times and enhancing multimodal understanding by over 30% [8]. - The self-feedback enhancement framework allows the model to self-improve, addressing challenges in data production and significantly reducing model hallucinations [13]. Group 3: Application Scenarios - In practical applications, Wenxin X1 Turbo demonstrates its capabilities in solving physics problems and generating code, with AI-generated code now accounting for over 40% of new code added daily [42][44]. - The technology supports over 100,000 digital human anchors, achieving a 31% conversion rate in live broadcasts and reducing broadcast costs by 80% [48]. Group 4: Market Potential and Future Directions - The global online education market is projected to reach 899.16 billion yuan by 2029, with large models playing a crucial role in this growth [49]. - The digital human market is expected to reach 48.06 billion yuan this year, nearly quadrupling from 2022, indicating significant opportunities for large model applications [49]. Group 5: Long-term Strategy and Vision - Baidu's approach to large models emphasizes continuous technological exploration and deepening, focusing on long-term value rather than short-term trends [57][58]. - The company maintains a dynamic perspective on the rapid evolution of technology, aiming to prepare for future industry transformations [58].

机器之心原创 作者：张倩 对于百度而言，既要保持长期主义的战略定力，也要在技术路径上灵活应变，这种「变与不变」的平衡或许正是其在这轮科技革命中的 制胜之道。 2025 年，模型能力的重要性依然无需多言。 从预训练的角度来看，虽然连 OpenAI 前首席科学家 Ilya Sutskever 都说，预训练数据即将用尽，但海量的图像、视频等多模态数据资源依然有待挖掘。 从后训练的角度来看，强化学习新范式正在让 Scaling Law 焕发新生， 新一代的推理模型在数学、代码、长程规划等问题上不断取得新进展。 对于 AI 公司来说，保持对基础模型研发的投入依然非常必要。现阶段来看，这仍然是攀登智能高峰的本质所在。 而在这个领域，百度一直是一个不可忽视的力量。从 2019 年发布文心大模型 1.0 至今， 文心大模型从知识和数据融合学习，到知识增强、知识点增强，从检索增 强、对话增强、逻辑推理增强，到慢思考、多模态的技术演进并非偶然，而是早期技术探索形成的「积淀」持续推动的结果。 正是这份「积淀」引领百度打造出 超越 GPT-4o 的多模态大模型文心 4.5 Turbo，以及领先 DeepSeek R1、V3 的深度思 ...