Group 1 - The core transition in algorithm technology is moving from "passive task handling" to "active evolution strategies," particularly in the financial sector, which is data and computation-intensive, presenting a historical opportunity for deep transformation [1] - Major global players are innovating algorithms to address the financial industry's challenges related to "long text, high real-time, and strong professionalism," with advancements such as OpenAI's GPT enhancing "long text causal reasoning" capabilities and Google's Gemini upgrading "multimodal dynamic interaction" algorithms [1] - The financial industry is shifting from merely applying open-source models to building a deep collaborative system of "scenarios-algorithms-data," creating knowledge barriers and deeply integrating industry scenarios to train effective agents for AI-native transformation of core business scenarios [1] Group 2 - The integration depth of "core business and AI" has become a core competitive advantage for financial institutions, with large models excelling in processing unstructured data and understanding intent in employee-facing scenarios [2] - In customer-facing applications, particularly in high-stakes areas like credit, risk control, and marketing, there are challenges such as low accuracy and delayed feedback, which can be addressed by specialized models that adapt to financial compliance and dynamic risk factors [2] - IDC predicts that the future will see a collaboration between general large models and specialized models, with AI solutions that manage and adapt to complex semantic understanding becoming mainstream in the financial sector [2] Group 3 - The development of large model toolchains is transitioning from "technology-driven" to "business-driven," enabling financial institutions to quickly build intelligent agents tailored to their specific business needs through low-code/no-code platforms [3] - Financial institutions are increasingly demanding intelligent agents in core areas such as investment research, credit decision-making, and risk management, which will create more value [3] - The collaborative management of "general models + specialized models" will become mainstream, with the core value of tool platforms being to lower the AI usage threshold for financial institutions, allowing business personnel to solve business problems using AI [3] Group 4 - The transition from "data-driven" to "knowledge-driven" is crucial for the AI-native application in finance, requiring the conversion of scattered data into reusable structured knowledge to meet the industry's high compliance, precision, and dynamism requirements [4] - Financial institutions aim to build a data flywheel by connecting end-to-end data flows, ensuring compliance through sensitive data classification, and integrating cross-modal data for collaborative analysis [4] - The construction of a data flywheel will enhance the breadth of knowledge, depth of reasoning, and robustness of financial intelligent systems, enabling rapid responses to changing business demands [4] Group 5 - The evolution from traditional computing to intelligent computing is essential for significantly improving computing efficiency, especially as large models evolve to trillion-parameter scales, leading to exponential growth in training computing requirements [5] - Efficient computing solutions, such as heterogeneous computing clusters and mixed training, are becoming critical for balancing cost and energy efficiency in response to the demands of ultra-large-scale models [5] - For different parameter scales, precise adaptation of computing solutions is necessary to optimize the match between computing resources and business needs, with specific strategies for billion-parameter models and trillion-parameter models [5]

她提到，百度面向整个游戏行业提供AI解决方案，尤其是在稳定性和容错方面提供保障。而在智能代 码方面，百度全栈编程智能体ZULU能够提升游戏研发效率，包括多工具集成调用、多模态高效交互、 多IDE完美适配、代码效果实时预览等特性。 "前段时间我们做了罗永浩的数字人直播，这个数字人克隆技术能够在游戏运营方面，比如游戏的IP在 不同场景下和用户进行互动，并提升玩家体验。"她表示。（罗宁） 专题：2025中国国际数码互动娱乐展览会（ChinaJoy） 8月1日至4日，第二十二届ChinaJoy将在上海新国际博览中心盛大启幕。百度集团副总裁袁佛玉在CDEC 高峰论坛发表演讲。她表示，AI在游戏行业的应用越来越多，算力的管理是游戏创新的必要保障。 新浪声明：所有会议实录均为现场速记整理，未经演讲者审阅，新浪网登载此文出于传递更多信息之目 的，并不意味着赞同其观点或证实其描述。 责任编辑：李昂 ...