Core Viewpoint - OpenAI's founder Sam Altman believes that the U.S. is underestimating the threat posed by China's next-generation artificial intelligence, and that chip regulations alone are not an effective solution [1][3] Group 1: AI Competition - Altman stated that China can develop faster in reasoning capabilities and has strengths in research and product development [3] - The AI competition between the U.S. and China is deeply intertwined, going beyond simple rankings [3] Group 2: OpenAI's Strategic Shift - OpenAI recently released its first open-weight models, gpt-oss-120b and gpt-oss-20b, marking a significant strategic shift from its long-standing closed-source approach [3] - The decision to release open-weight models was influenced by competition from Chinese models, such as DeepSeek and Kimi K2 [3] - Altman emphasized that if OpenAI did not act, Chinese open-source models would gain widespread adoption, making this a significant factor in their decision [3]

Group 1: Photovoltaic Industry - The Ministry of Industry and Information Technology (MIIT) is actively coordinating between power generation companies and local industries to enhance price transmission from manufacturing to power stations, emphasizing a market-oriented and legal approach to eliminate outdated production capacity [1] - The average bidding price for components from China Resources and China Huadian has increased by 5-8% month-on-month, while silicon material companies have proactively limited production, leading to a 10% decrease in silicon wafer inventory over two weeks [1] - The investment sequence indicates a tight supply of silicon materials in Q3, a premium for BC battery technology in Q4, and a simultaneous increase in both volume and price of auxiliary materials such as glass and adhesive films [1][2] Group 2: Solid-State Battery Technology - A breakthrough in solid-state battery technology has been achieved with the introduction of 5μm vapor-deposited lithium anodes, significantly reducing dendrite risk and achieving over 500 cycles with a capacity retention rate above 90% [3] - The cost of 5μm vapor-deposited lithium is projected to drop to 2 million yuan per GWh, compared to 4 million yuan for 20μm rolled lithium foil, indicating a substantial cost reduction in the industry [3] - The solid-state battery market could reach 50-100 billion yuan by 2030, driven by the demand for 100GWh of global solid-state battery production [3] Group 3: Robotics Industry - The T-Link Gen3 technology is reshaping the supply chain with a focus on lightweight materials, energy efficiency, and sensor integration, leading to a re-tendering of motors, reducers, and lead screws [4] - The use of PEEK materials has reduced costs by 30% compared to imports, and the new harmonic magnetic field motors have achieved a 50% reduction in size while doubling power density [5] - The 3D vision solution from Orbbec has a single machine value of 200 USD, and the company has passed factory audits [6] Group 4: Semiconductor and AI Models - The DeepSeek model has been upgraded to V3.1, expanding the context length from 64K to 128K, which is expected to increase demand for GPU memory and HBM [7] - The need for larger training clusters is anticipated to rise by 30%, benefiting semiconductor and storage manufacturers such as Cambricon, Haiguang, and Lanke [7] Group 5: Pharmaceutical Industry - Rongchang Biotech has licensed its ophthalmic drug RC28-E to Japan's Santen Pharmaceutical, marking a shift in domestic innovative drug licensing from popular fields like oncology to specialized areas with differentiated advantages [8] - This collaboration model provides a clear path for value realization in less popular biotech sectors through upfront payments, milestones, and sales sharing, enhancing cash flow and leveraging established commercialization channels [8] Group 6: High-Speed Rail Industry - The China National Railway Group has initiated its second batch of high-speed train tenders for the year, with 210 sets, marking a recent high and exceeding market expectations [9] - This move reinforces the trend of sustained railway investment recovery, with new construction and maintenance peaks positively impacting the performance certainty of core companies in the industry [9]

来源：环球网 【环球网科技综合报道】8月20日消息，DeepSeek日前在Hugging Face上开源了新模型 V3.1-Base。 此外，日前DeepSeek 还发布通知称，线上模型版本已升级至 V3.1，上下文长度拓展至 128k，可通过官 方网页、App、小程序测试，API 接口调用方式保持不变。 就在8月14日，DeepSeek App发布了1.3.0版本，此次更新在修复已知问题、优化文本操作体验的基础 上，首次引入"对话内容生成分享图"功能，为用户提供更便捷、个性化的内容传播方式。（思瀚） ...

就在昨晚，DeepSeek官方悄然上线了全新的V3.1版本，上下文长度拓展到128k。 对于这波更新，大家的热情可谓是相当高涨。 即便还未公布模型卡，DeepSeek V3.1就已经在Hugging Face的趋势榜上排到了第四。 本次开源的V3.1模型拥有685B参数，支持多种精度格式，从BF16到FP8。 综合公开信息和国内大咖karminski3的实测，V3.1此次更新亮点有： 编程能力：表现突出，根据社区使用Aider测试数据，V3.1在开源模型中霸榜。 性能突破：V3.1在Aider编程基准测试中取得71.6%高分，超越Claude Opus 4，同时推理和响应速度更快。 原生搜索：新增了原生「search token」的支持，这意味着搜索的支持更好。 架构创新：线上模型去除「R1」标识，分析称DeepSeek未来有望采用「混合架构」。 成本优势：每次完整编程任务仅需1.01美元，成本仅为专有系统的六十分之一。 值得一提的是，官方群中强调拓展至128K上下文，此前V3版本就已经支持。 | Model | #Total | #Activated | Context | Download | | --- ...

没等到Deepseek R2，DeepSeek悄悄更新了V 3.1。 官方群放出的消息就提了一点，上下文长度拓展至128K。128K也是GPT-4o这一代模型的处理Token的长度。因此一开始，鲸哥以为从V3升级到V 3.1，以 为是不大的升级，鲸哥体验下来还有惊喜。 代码能力与前端审美提升 从开源社区Huggingface上传的模型版本看，模型尺寸达685B，支持 BF16、F8_E4M3、F32 等张量类型，平衡模型的计算精度和效率。 最惊喜的是代码能力提升明显，前端审美也有大幅度提升。我们先看V3.1在代码测试中的变现。 请设计并开发一款结合日历和待办事项（To-Do）的产品，其核心功能应包括： 任务分类与颜色标记：用户能够创建不同类别的任务，并为每个类别分配独特的颜色。当任务被归类后，其在日历视图上应以相应的颜色进行标记，以便 快速识别。短期任务管理：*完成标记： 对于计划在特定日期完成的任务，用户应能将其标记为"已完成"。已完成的任务应在界面上以视觉方式（例如， 划掉、变灰或显示完成图标）清晰区分。*逾期处理： 如果任务未在计划日期完成，系统应提供明确的视觉提示（例如，颜色变化、闪烁或标记为逾 期） ...

上方为DeepSeek-V3-0324开源网页，下方为DeepSeek-V3.1-Base开源网页 开源地址： https://huggingface.co/deepseek-ai/DeepSeek-V3.1-Base 智东西第一时间在网页端对新模型的能力进行了体验，从初步体验结果来看，这一模型在编程（尤其是前端能力）、物理定律理解、创意写 作、数学、回答语气等方面都出现不同程度的提升和变化。 以下是智东西体验的部分案例： 此外，DeepSeek还将App、网页端的"深度思考（R1）"字样改为了"深度思考"，有网友猜测这是融合推理模型与非推理模型的征兆，但 DeepSeek官方尚未发布任何关于这一改动的消息。 左侧为旧版页面，右侧为新版页面 这一模型现已上传至Hugging Face，不过目前仅开源了未经指令微调的Base版本（基础模型），其配置文件、脚本代码和模型权重均可供下 载。与DeepSeek-V3-0324相比，模型参数量、张量类型没有明显变化。 智东西8月20日报道，昨日晚间，DeepSeek在官方群宣布：DeepSeek线上版本模型已升级至DeepSeek V3.1，上下文窗口从原有的64k扩展 ...

Group 1 - DeepSeek has upgraded its online model to version 3.1, expanding the context length to 128k [1] - Alibaba's Tongyi Qianwen has launched an image editing model called Qwen-Image-Edit [1] - Nvidia has released a small language model named Nemotron-Nano-9B-v2 [1] Group 2 - Xiaopeng Motors' chairman He Xiaopeng announced that humanoid robots and L4-supported vehicles are expected to be mass-produced by 2026 [3] - Nvidia is collaborating with Foxconn to develop a humanoid robot, which is expected to debut in November [1] - Figure's founder indicated that Helix is set to undergo a significant upgrade [1] - Arm has hired Amazon's AI chip head Rami Shino to support its self-developed chip initiatives [1]

Core Viewpoint - The online model version of DeepSeek has been upgraded to V3.1, expanding the context length to 128K, while maintaining the same access methods through the official website, app, mini-program, and API calls [1] Group 1 - DeepSeek's online model has been upgraded to version 3.1 [1] - The context length has been expanded to 128K [1] - Access methods remain unchanged, including the official website, app, mini-program, and API [1]

Group 1 - The core focus of the recent update is the expansion of context length, which has been increased to 128k, allowing for improved memory and processing capabilities [1][3] - Users have reported enhancements in front-end coding capabilities following the update [1][3] - There are rumors regarding the potential release of DeepSeek R2 in late August, but no official release date has been confirmed [3]

Core Viewpoint - DeepSeek has upgraded its online model to version 3.1, expanding the context length to 128k [1] Company Summary - The upgrade to version 3.1 indicates a significant enhancement in the capabilities of DeepSeek's online model, allowing for a larger context length which can improve the model's performance and usability [1]