在DeepSeek-R1发布一周年之际，新模型"MODEL1"的项目名在开源社区悄然出现。近日，DeepSeek官 方在GitHub更新了一系列FlashMLA代码，项目文件有数十处都提到了此前未公开的"MODEL1"大模型 标识符。 | a deepseek-ai / FlashMLA | | | | | | | O N | | --- | --- | --- | --- | --- | --- | --- | --- | | <> Code G Issues 66 | I'l Pull requests | 26 | Actions H Projects | Security | ~ Insights | | | | जा Files | | | FlashMLA / csrc / sm90 / decode / sparse_fp8 / instantiations | | | P | | | nieun & | P Q | 1 | interestingLSY Multiple updates and refactorings (#150) | | 1 | | | | Q Go to file | | ...

Core Insights - DeepSeek has updated its official GitHub repository with a series of FlashMLA code, drawing attention to a model named "Model 1" [1][2] - Model 1 is speculated to be the new model code that DeepSeek is expected to release around the Chinese New Year [2] Model Specifications - Model 1 is one of the two main model architectures supported in DeepSeek FlashMLA, alongside DeepSeek-V3.2 [2] - It is likely to be an efficient inference model with lower memory usage compared to V3.2, making it suitable for edge devices or cost-sensitive scenarios [2] - Model 1 may also function as a long-sequence expert optimized for sequences longer than 16K, making it ideal for tasks such as document understanding and code analysis [2]

你是一个非常有创意的普通人，你曾经有一个梦想，希望把自己脑海中的点子都用视觉形态展示，比如 拍成动画、电影、电视剧等等。但你苦于资金和资源，无法实现。直到看到PixVerse R1后，你感觉到， 自己的梦想好像要成真了。 1月13日，国内AI视频初创公司爱诗科技发布了一款通用实时世界模型PixVerse R1；本周，该模型已升 级支持HD画质。众多关注AI视频的大咖惊叹：AI视频行业的DeepSeek时刻到了。 PixVerse R1改变了视频生成的逻辑。之前，用户需要输入文字或图片生成视频，还需要等待几秒钟甚至 几分钟。但使用PixVerse R1，用户即使不输入提示词，PixVerse R1也会自动生成视频，它就像一个能无 限生成内容的数字世界，可以让人沉浸遨游。在这个世界里，用户的提示词有一种言出法随的效果，输 入的指令有多快，PixVerse R1画面的改变就有多快。 在YouTube上，已经有普通用户用它生成了一部90分钟的电影。看到PixVerse R1价值的影视公司已经开 始行动。1月19日，中国儒意战略投资爱诗科技，双方也宣布进行版权共享，建立包括影视、游戏、流 媒体等多方面的战略合作伙伴关系 ...

Core Insights - DeepSeek plans to launch its next-generation flagship AI model, DeepSeek V4, around mid-February during the Lunar New Year, which is expected to significantly enhance coding capabilities and attract industry attention [1][2] Group 1: Model Development - The release of DeepSeek V4 follows the one-year anniversary of the DeepSeek-R1 model, with developers discovering updates related to FlashMLA in 114 files, including 28 references to an unknown "MODEL1" identifier, likely indicating a new AI model with a different architecture [1][2] - The new architecture optimizes key technical aspects such as key-value (KV) cache layout, sparsity handling, and FP8 data format decoding support, addressing memory usage and computational efficiency issues, thereby laying the groundwork for performance improvements [3] Group 2: Research Innovations - DeepSeek's research team has previously published two technical papers introducing innovative training methods like "optimized residual connections (mHC)" and a biologically inspired "AI memory module (Engram)," suggesting that DeepSeek V4 may integrate these latest research findings to enhance its capabilities in handling complex tasks [3]

Core Insights - DeepSeek has unveiled a new model architecture named "MODEL1" as part of its FlashMLA software, which is designed to optimize large model inference generation on NVIDIA GPUs [1][2] - MODEL1 is expected to be a highly efficient inference model with lower memory usage compared to the existing V3.2 model, making it suitable for edge devices and cost-sensitive applications [2] - The company is set to launch its next flagship AI model, DeepSeek V4, in mid-February 2025, which is anticipated to enhance coding capabilities [3] Group 1 - The FlashMLA tool analyzes a total of 114 code files and identifies the MODEL1 architecture mentioned 31 times [1] - MODEL1 supports multiple GPU architectures, including specific implementations for NVIDIA H100/H200 and B200, indicating a tailored optimization for the latest GPU technology [2] - DeepSeek's existing models represent two technical routes: the V series focusing on comprehensive performance and the R series targeting complex reasoning tasks [2] Group 2 - The V3 model, launched in December 2024, established a strong performance foundation with its efficient MoE architecture, followed by rapid iterations leading to V3.2 [3] - The R1 model, released in January 2025, excels in complex reasoning tasks through reinforcement learning and introduces a "deep thinking" mode [3] - Recent technical papers from DeepSeek suggest ongoing development of new models that may integrate innovative training methods and AI memory modules [3]

Core Insights - The article discusses the significant impact of the release of DeepSeek R-1 on the global open-source AI ecosystem, marking a pivotal moment for China's AI development and its influence worldwide [1][3]. Group 1: Transformation of AI Landscape - The release of DeepSeek R-1 in January 2025 is identified as a watershed moment that lowered barriers to technology and application, leading to a shift from closed-source to open-source models in China [1][5]. - Major Chinese tech companies like Baidu, Alibaba, and Tencent, along with startups like Moonshot, have significantly increased their open-source investments, resulting in Chinese models surpassing U.S. models in download volume on Hugging Face [1][6]. Group 2: Breaking Down Barriers - DeepSeek R-1 effectively dismantled three critical barriers: technical, adoption, and psychological, transforming the perception of open-source from a tactical choice to a long-term strategy for Chinese tech companies [3][5]. - The article emphasizes that the focus of competition has shifted from individual model performance to ecosystem development, with companies now prioritizing engineering systems and application scenarios [6][10]. Group 3: Market Dynamics and Global Response - The article notes that the rise of Chinese AI models is not merely a result of collaboration but is driven by shared technological, economic, and regulatory pressures, leading to a competitive alignment among companies [8][11]. - Global reactions indicate a reliance on Chinese-developed models, with many startups and researchers defaulting to these models, highlighting the growing influence of Chinese AI in international markets [11].

【市场复盘】 【热门ETF】 机器人ETF(562500)是全市场唯一规模超两百亿、流动性最佳、覆盖中国机器人产业链最全的机器人主 题ETF，助力投资者一键布局中国机器人产业。 2.瑞士百达多元资产香港区主管黄思远表示，还是会持续投资科技股，尽管苹果、微软有点跑输大市， 不过很多科技公司都很不错。目前美国市场对于科技领域专注于"现在交付"，而中国市场略有不同，人 们花钱购买机器人等，也是更长期的购买。目前这一市场还没有看到过度繁荣及不合理的繁荣。 3.德勤发布《2026科技、传媒和电信行业预测》报告指出，AI正在重新定义硬件、软件、电信与传媒行 业的基础。全球工业机器人装机量预计将在2026年达到550万台，并保持相对温和的年增长率，突破每 年100万台的关键节点预计要到2030年之后。 【机构观点】 招商证券认为，震裕科技（300953）利基的模具业务经营稳中有增，铁芯板块的新产品开始放量，有望 恢复到较好的增速。收入体量最大的结构件业务经营如期反转，有望维持加快增长态势。公司大力培育 的机器人板块，在国内市场进展较顺利，后续海外大客户体系也有望有所突破。 本周二(1月20日)，科创人工智能ETF华夏(58 ...

DeepSeek-R1发布一周年之际，新模型"MODEL1"曝光。DeepSeek在GitHub更新FlashMLA代码，横跨 114个文件中有28处提到MODEL1，与V32作为不同的模型出现。已知V32是DeepSeek-V3.2，MODEL1 很可能是新的架构。代码中的具体差异体现在KV缓存布局、稀疏性处理和FP8解码方面，在内存优化 上有多处不同。此前有消息称DeepSeek将在2月中旬春节前后发布下一代旗舰模型。 ...

Core Insights - European AI companies are seeking to innovate and reduce reliance on American technology amid rising geopolitical tensions with the U.S. [4] - The success of the Chinese AI startup DeepSeek has inspired European researchers to explore alternative paths for developing competitive AI products [5] - European governments are committing hundreds of millions of dollars to decrease dependence on foreign AI suppliers [5] Group 1: Current Landscape - U.S. companies dominate the AI industry across various segments, including processor design, data center capacity, and application development [4] - The perception that innovation is solely occurring in the U.S. is considered dangerous, as it may discourage European efforts to compete [5] - European AI labs may have an advantage in open research and development, allowing for collaborative improvements on models [5] Group 2: Urgency for Autonomy - The changing geopolitical landscape has heightened the urgency for Europe to achieve self-sufficiency in AI technology [6] - Tensions between European leaders and the Trump administration have raised concerns about the future of NATO and the reliance on U.S. technology [6][7] - European dependence on U.S. AI services is viewed as a potential liability in trade negotiations [7] Group 3: Strategies for Development - European countries are attempting to localize AI development through funding initiatives, regulatory adjustments, and partnerships with academic institutions [8] - There is a focus on creating competitive large language models tailored for European languages [8] - The ongoing success of U.S. platforms like ChatGPT poses a challenge for European AI companies to catch up [9] Group 4: Policy and Market Dynamics - There is ambiguity regarding how far Europe intends to push for "digital sovereignty" and whether it requires complete self-sufficiency or just local alternatives [10] - Some European suppliers advocate for strategies that prioritize local AI products, while others warn against excluding U.S. companies [10] - The consensus on policy measures to achieve self-sufficiency in AI is still lacking within Europe [10] Group 5: Future Aspirations - Despite limited budgets, European AI labs believe they can close the performance gap with U.S. leaders, as demonstrated by DeepSeek [11] - Projects like SOOFI aim to develop competitive language models with around 100 billion parameters [11] - The future progress in AI may not solely depend on the largest GPU clusters, indicating a shift in the competitive landscape [11]

Group 1 - The core idea of the article is that the brain-computer interface (BCI) sector is gaining significant attention and investment, with major developments from companies like Neuralink and Qiangnao Technology, indicating a potential commercial breakthrough in the near future [1][30][11] - Neuralink plans to begin large-scale production by 2026, while Qiangnao Technology has completed a financing round of 2 billion yuan and submitted an IPO application to the Hong Kong Stock Exchange [1][30][11] - The BCI technology is not new, having been conceptualized as early as 1973, but recent advancements have made it more viable for applications such as movement reconstruction and cognitive enhancement [1][31][36] Group 2 - Neuralink has made significant progress in invasive BCI technology, reducing the time to implant a single electrode from 17 seconds to 1.5 seconds and conducting 12 clinical studies with over 10,000 patients waiting for treatment [5][36] - Qiangnao Technology is pursuing a non-invasive approach, which allows for brain signal collection without surgery, potentially expanding its applications to entertainment and gaming [7][39][41] - The market for BCIs is projected to reach $400 billion in the U.S. medical sector by 2045, with the overall market expected to exceed $1 trillion [12][43] Group 3 - Both Neuralink and Qiangnao Technology face significant challenges, including the immaturity of the technology, high costs, and privacy concerns [15][47][56] - The technology is still developing, with current methods only able to record signals from a limited number of neurons, and invasive methods face risks of infection and device failure [49][50] - The costs associated with BCI technology, including device and surgical expenses, are currently high, which could limit accessibility and market growth [21][53][55] Group 4 - Companies are seeking capital to expand production and reduce costs, with Neuralink raising $650 million in its Series E funding and Qiangnao Technology securing 2 billion yuan in its Pre-IPO round [24][56] - Qiangnao Technology aims to assist 1 million individuals with mobility impairments and 10 million patients with cognitive disorders over the next 5 to 10 years [26][58] - Privacy issues surrounding data collection from BCIs need to be addressed, as the data could involve sensitive personal information [26][60]