Core Viewpoint - The company, Yunzhisheng (09678), has made significant progress in the commercialization of its foundational large model and intelligent agent platform, collaborating with well-known domestic enterprises to implement projects valued at nearly RMB 200 million, with delivery planned by the end of 2025 [1] Group 1 - The company has established deep cooperation with domestic partners to advance its foundational large model and intelligent agent projects [1] - The implementation of these projects is based on the company's proprietary computing scheduling platform, Shanhai large model, and Shouya Agent intelligent platform [1] - This progress signifies a solid step forward in the commercialization process of the company's foundational large model and intelligent agent platform [1] Group 2 - The advancements further validate the company's technological leadership in foundational large models and intelligent agent platforms [1] - The company plans to deepen its research and commercialization efforts in the smart living sector, leveraging its strong advantages [1]

Core Insights - The company, Yunzhisheng (09678.HK), has made significant progress in the commercialization of its foundational large model and intelligent agent platform [1] - The company has partnered with well-known domestic enterprises to implement projects valued at nearly RMB 200 million, utilizing its proprietary computing scheduling platform, Shanhai large model, and Shouya Agent intelligent platform [1] - The delivery of these projects is planned to be completed by the end of 2025, indicating a solid step forward in the commercialization process [1] Company Developments - The advancements signify the recognition of the company's technological leadership in foundational large models and intelligent agent platforms [1] - The company aims to further deepen its research and commercialization efforts in the smart living sector, leveraging its strong advantages [1]

Core Insights - The company, Yunzhisheng (09678), has made significant progress in the commercialization of its foundational large model and intelligent agent platform [1] - The company has partnered with well-known domestic enterprises to implement projects valued at nearly RMB 200 million, with delivery planned by the end of 2025 [1] - This advancement indicates the company's leading position in the technology of foundational large models and intelligent agent platforms [1] Summary by Categories Commercialization Progress - The company has achieved substantial progress in the commercialization of its foundational large model and intelligent agent platform [1] - The implementation of projects worth approximately RMB 200 million is underway, showcasing the company's ability to attract significant partnerships [1] Technological Leadership - The advancements signify further recognition of the company's technological leadership in foundational large models and intelligent agent platforms [1] - The company plans to deepen its research and commercialization efforts in the smart living sector, leveraging its strong advantages [1]

UNISOUND AI TECHNOLOGY CO., LTD. 雲知聲智能科技股份有限公司 （於中華人民共和國註冊成立的股份有限公司） （股份代號：9678） 香港交易及結算所有限公司及香港聯合交易所有限公司對本公告的內容概不負責，對其準確性或完整性亦不發表 任何聲明，並明確表示概不就因本公告全部或任何部分內容而產生或因倚賴該等內容而引致的任何損失承擔任何 責任。 本公告乃由雲知聲智能科技股份有限公司（「本公司」）自願作出，旨在知會本公司股東 及潛在投資者有關本公司的最新業務發展情況。 本公司董事會（「董事會」）欣然宣佈，本公司基礎大模型和智能體平台商業化取得實質 性進展，近日與國內知名企業等合作夥伴深入合作，將基於自有知識產權的算力調度平 台、山海大模型以及獸牙Agent智能體平台，實現價值近人民幣2億元的基礎大模型和智 能體項目實施部署，計劃將於2025年底前完成交付。 該進展意味著本公司在基礎大模型和智能體平台商業化落地進程中邁出了堅實的一步， 同時也標誌著公司基礎大模型和智能體平台技術的領先性得到進一步認可。本公司將 在具備深厚優勢的智慧生活領域進一步深耕大模型和智能體的研發及商業化落地。 承董事會 ...

Core Insights - The rapid development of the AI industry is accelerating iterations across various sectors, presenting significant industrial opportunities [3] - The scale of the AI industry is projected to be at least 100 times larger than the previous generation, indicating substantial growth potential [5] Group 1: Trends in AI Development - The first major trend is the transition from discriminative AI to generative AI, now evolving towards agent-based AI, with task lengths doubling and accuracy exceeding 50% in the past seven months [7] - The second trend indicates a slowdown in the scaling law during the pre-training phase, with more focus shifting to post-training stages like reasoning and agent applications, while reasoning costs have decreased by 10 times [7] - The third trend highlights the rapid advancement of physical and biological intelligence, particularly in the intelligent driving sector, with expectations for 10% of vehicles to have L4 capabilities by 2030 [7] Group 2: AI Risks and Industry Structure - The emergence of agent-based AI has significantly increased AI risks, necessitating greater attention from global enterprises and governments [8] - The fifth trend reveals a new industrial structure characterized by foundational large models, vertical models, and edge models, with expectations for 8-10 foundational large models globally by 2026, including 3-4 from China and the same from the U.S. [8] - The future is anticipated to favor open-source models, with a projected ratio of 4:1 between open-source and closed-source models [8]

Core Insights - The rapid development of the AI industry is accelerating iterations across various sectors, presenting significant industrial opportunities [1] Group 1: Trends in AI Industry - The first major trend is the transition from discriminative AI to generative AI, now evolving towards agent-based AI, with task length doubling and accuracy exceeding 50% in the past seven months [3] - The second trend indicates a slowdown in the scaling law during the pre-training phase, shifting focus to post-training stages like inference and agent applications, with inference costs decreasing by 10 times while computational complexity for agents has increased by 10 times [3] - The third trend highlights the rapid development of physical and biological intelligence, particularly in the smart driving sector, predicting that by 2030, 10% of vehicles will possess Level 4 autonomous driving capabilities [3] Group 2: Future Projections and Risks - The fourth trend points to a significant rise in AI risks, with the emergence of agents increasing risks at least twofold, necessitating greater attention from global enterprises and governments [4] - The fifth trend reveals a new industrial landscape for AI, characterized by a combination of foundational large models, vertical models, and edge models, with expectations that by 2026, there will be approximately 8-10 foundational large models globally, including 3-4 from China and 3-4 from the U.S. [4] - The future is expected to favor open-source models, with a projected ratio of 4:1 between open-source and closed-source models [4]

Core Insights - The AI industry is rapidly evolving, leading to accelerated iterations across various sectors, with significant opportunities arising from the integration of information, physical, and biological intelligence [1]. Group 1: Trends in AI Development - The first trend is the transition from discriminative AI to generative AI, now moving towards agent-based AI, with task lengths doubling and accuracy exceeding 50% in the past seven months [3]. - The second trend indicates a slowdown in the scaling law during the pre-training phase, shifting focus to post-training stages like inference and agent applications, while the overall intellectual ceiling continues to advance [3]. - The third trend highlights the rapid development of physical and biological intelligence, particularly in the smart driving sector, predicting that by 2030, 10% of vehicles will possess Level 4 autonomous driving capabilities [3]. Group 2: AI Risks and Industry Structure - The fourth trend points to a significant increase in AI risks, with the emergence of agent-based AI doubling the associated risks, necessitating greater attention from global enterprises and governments [4]. - The fifth trend reveals a new industrial landscape characterized by foundational large models, vertical models, and edge models, with expectations that by 2026, there will be around 8-10 foundational large models globally, with China and the US each having 3-4 [4]. - The future is expected to favor open-source models, with a projected ratio of 4:1 between open-source and closed-source models [4].

Group 1 - The State Council of China has issued an opinion to accelerate the development of the "Artificial Intelligence +" industry, emphasizing the importance of AI in various sectors [1][3] - The opinion outlines a comprehensive framework for the AI industry, covering foundational, model, and application layers, and highlights the rapid iteration of foundational large models [1][5] - The document introduces new technologies, business models, and paths for intelligent transformation across primary, secondary, and tertiary industries, aiming to enhance industrial efficiency through AI [3][14] Group 2 - A large model focused on process industries such as steel, non-ferrous metals, chemicals, and building materials has been launched, with over 130 leading industry companies forming the "Industrial AI Data Alliance" to promote data application and service sharing [5] - The rapid advancement of large models in China is noted, with improvements in foundational capabilities, reasoning abilities, and multimodal understanding and generation [7] - In Guizhou, a complete data labeling industry chain has emerged, fostering innovation and collaboration across the industry [9] Group 3 - The digital labeling business in Guizhou is projected to grow from 70 million in 2024 to 150 million in 2025, and further to 300 million in 2026, indicating significant market potential [11] - An industrial acceleration center in Shenyang, in collaboration with iFlytek, has incubated nearly 150 service enterprises, generating a cumulative output value of 1.1 billion [11] - The AI field is experiencing three new trends: diversification of intelligent forms, elevation of capabilities, and systematization of technology [13]

新华财经上海7月25日电 在2025世界人工智能大会（简称＂ WAIC 2025"）开幕前夕，上海阶跃星辰智 能科技有限公司25日发布了新一代基础大模型Step 3。阶跃星辰同时还联合国内多家芯片、平台厂商发 起成立"模芯生态创新联盟"，将通过推动模型和芯片产业链联合创新，加速大模型应用落地。 阶跃星辰专注于基础大模型的研发，持续推进模型的技术迭代。阶跃星辰创始人、首席执行官姜大昕表 示："随着大模型进入到强化学习发展阶段，新一代推理模型成为主流，模型性能的提升固然显著，但 这是否完全等同于模型价值？面对这一产业之问，我们必须回归客户需求，立足真实应用场景，探索大 模型创新落地的可行路径。这是我们研发新一代Step 3基础模型的出发点。" 随着大模型技术迈向推理时代，阶跃星辰提出，最适合实际应用的大模型需要满足强智能、低成本、可 开源和多模态四个特征。基于这样的研发理念，阶跃星辰打造了新一代基础模型Step 3，专为追求性能 与成本均衡的企业和开发者设计。阶跃星辰同时宣布Step 3将在7月31日面向全球企业和开发者开源， 为开源世界贡献多模态推理模型。 要让大模型真正能用起来，需要从模型、芯片、平台到应用的 ...

Core Insights - The company Jieyue Xingchen has launched its next-generation foundational model, Step3, which emphasizes multimodal reasoning capabilities [1] - The Step3 model achieves up to 300% efficiency in 32K context reasoning on domestic chips compared to DeepSeek R1 [1] - The Step3 model is planned to be open-sourced globally on July 31 [1]