将投中网设为"星标⭐"，第一时间收获最新推送 中国VC也一样。 作者丨 董师傅 来源丨 投中网 今天蒲凡他们发了一期音频节目。里边夸了曹曦招人待见，以及美元 VC 回来了这些话。我上期节目就是看了这 篇稿子，才说不喜欢曹毅曹曦两位老板，我跟他们的看法是有分歧的，或者说标准是不同的，不过投中网就这 样，你有你的看法，我有我的，我会把我的标准摆出来，但听不听都行，人和人没有共识，我早就接受了。投中 网有些内容跟我价值观没那么一致，这也没什么可辩驳的，我当主编，底线之上就行，有问题还是我买单。当然 了，我自己的表达也不需要谁替我承担，我批评谁我吹捧谁，也是我自己为自己负责。 今天正好借这个话题谈谈美元基金和硅谷。 先从沈南鹏、张颖、曹毅、曹曦四位聊起。 首先解释一下我的看法。 在我看来，曹毅的品牌思路还是红杉的子集，而曹曦则是在走经纬的路子。 拿曹毅来说，他在讲话、表达、处世，以及投资策略上，都有很重的沈南鹏的影子。比如以前底片写过，他是 VC2.0 里规模化打法最坚决的，就是用规模加杠杆，出来先投贝壳这种中后期的案子。而品牌上也很像。我对他 和沈南鹏的表达的理解，都是 " 先知 " 式的。做个不恰当的比喻是上神龛 ...

以下文章来源于TOP创新区研究院 ，作者人才研究组 TOP创新区研究院 . 创新区研究，就在TOP研究院。TOP研究院专注于全球创新区的一体化研究，从Talent(个人), Organization(组织), Place(区域)三大维度出发，通过"研究/连接/分享"，探索中国创新区的实践路径。 本文来自微信公众号： TOP创新区研究院 ，作者：TOP创新区研究院、FTA Group，题图来自：AI 生成 最近，我们看到Y Combinator （YC） 校友、现任Orange Collective合伙人Jason Freedman发了一 条有意思的推文。 作为曾经阅读过8000份YC申请的资深评审，Jason说到，在YC内部的复盘中，他们做了一个极为硬 核的"回测"： 将那些最成功公司的早期申请表翻出来，看看如果严格按照标准问题来打分，它们是否会被淘汰。 结果是惊人的。 这些千亿美金的巨头，大部分会在第一轮就被扔进碎纸机。 如果我们问"这主意好吗？"，Airbnb就该死在摇篮里； 如果我们问"市场大吗？"，Coinbase和Nvidia在起步时简直渺小得可笑。 当然，这不是眼光的问题，这是风险投资行业的一个系 ...

2025第十五届高工锂电年会 ◎李子健 记者 王玉晴 11月20日下午，在2025第十五届高工锂电年会闭幕式专场上，锂电龙头企业董事长展开接力演讲。现场 座无虚席，连过道都站满了热情的观众，想要第一时间了解龙头企业对形势的研判。 从现场来看，企业家们认可了锂电行业的复苏与市场需求的长期确定性。"行业形势好了，今晚的酒是 甜的。"龙蟠科技董事长石俊峰说。"锂电行业的需求、方法论、全球化都是确定的。"远景能源中国区 总裁赵卫军表示。 赵卫军分析认为，未来十年，锂电产业具备确定的周期性机遇。机遇的来源是新能源消纳、人工智能数 据中心（AIDC）方面的驱动和电力系统的安全需求。 新能源消纳方面，到2035年中国风电和太阳能发电总装机容量将达到2020年的6倍以上，力争达到36亿 千瓦，新能源消纳进入关键瓶颈期，需要储能作为支撑。AIDC方面，以美国市场为例，短周期内需提 升25%的发电量。这一方面依靠天然气发电，另一方面就需要风光发电，进而需要大量配储。在电力系 统安全方面，欧洲的能源独立需要新能源加储能支撑。 "以上需求支撑起了锂电产业发展的确定性。"赵卫军预测，风光发电很快会进入0.1元/度的时代。预计 到203 ...

Group 1 - The core viewpoint emphasizes the importance of closely tracking industry dynamics to capture investment opportunities in the technology sector, which combines long-term growth potential with rapid iteration characteristics [1] - The newly launched Huazhong New Energy Mixed Fund aims to discover growth opportunities in technology, with a focus on disruptive innovation and cyclical trends [1] - The fund manager, Xu Hantian, has a strong background in microelectronics and the semiconductor industry, which enables him to identify industry changes and core competitive advantages [1][2] Group 2 - The fund will balance certainty and high odds in investment opportunities, focusing on high-odds targets while ensuring a solid foundation of certainty [2] - The investment strategy includes analyzing technology penetration rates and capacity cycles to predict industry turning points and assess supply-demand relationships [2] - The core of technology lies in disruptive innovation, which significantly enhances productivity and requires attention to market needs and the feasibility of commercial implementation [2] Group 3 - Xu Hantian views the core logic of investing in the technology sector as the penetration of AI technology across various industries, with a focus on the AI computing power industry chain [3] - The investment focus is shifting towards application implementation and performance realization as AI model capabilities continue to improve [3] - The structural market trend driven by technological innovation is expected to be the main theme in the market for the next decade, significantly impacting various industries [3]

Core Viewpoint - The collaboration between NVIDIA and Intel, marked by NVIDIA's $5 billion investment in Intel and the development of the "Intel x86 with RTX" chip, signifies a major shift in the semiconductor industry after decades of rivalry, potentially reshaping the competitive landscape [4][30]. Group 1: Historical Context - NVIDIA was founded in 1993 by Jensen Huang and his partners, who identified a growing demand for graphics processing as PCs became more popular [7][8]. - Initially, NVIDIA struggled to gain traction in a market dominated by Intel, which held over 80% of the CPU market share in the early 1990s [8]. - The introduction of NVIDIA's GeForce 256 in 1999 marked a turning point, establishing NVIDIA as a key player in the GPU market [10]. Group 2: Competitive Dynamics - The early 2000s saw NVIDIA's rise as it introduced technologies like Optimus, which allowed for intelligent switching between integrated and dedicated graphics, further embedding its products in the PC ecosystem [11]. - Intel's initial indifference to the GPU market shifted as it recognized the growing importance of GPUs, leading to legal battles and competitive tensions between the two companies [14][15]. - By 2010, NVIDIA had established a stronghold in the high-end GPU market, while Intel focused on integrated graphics, leading to a stable division of market roles [17]. Group 3: Technological Evolution - The decline of Moore's Law around 2005 forced Intel to reassess its strategies, while NVIDIA capitalized on the rise of parallel computing through its CUDA architecture, transforming GPUs into general-purpose computing platforms [19][20]. - The emergence of AI in 2012, highlighted by the success of deep learning models using NVIDIA GPUs, solidified NVIDIA's position as a leader in AI computing [22][24]. Group 4: Market Positioning - By 2024, NVIDIA's market capitalization soared to $3 trillion, surpassing major tech companies, while Intel faced significant losses and market share erosion [24][30]. - The partnership between NVIDIA and Intel is seen as a strategic move to leverage each other's strengths in a rapidly evolving market, although the future dynamics remain uncertain due to emerging competitors like AMD and the rise of specialized chips [33][34]. Group 5: Geopolitical Factors - Geopolitical tensions, particularly between the U.S. and China, have influenced the semiconductor landscape, with both companies needing to navigate these complexities as they pursue their strategic goals [34][35].

Group 1 - Shanghai Future Industry Fund has successfully completed its expansion, increasing its scale from 10 billion to 15 billion yuan, with 8 billion yuan already paid in [1] - The fund has invested in cutting-edge fields such as controllable nuclear fusion, quantum computing, AI for Science, and brain-computer interfaces [1] - The next steps for the fund include focusing on disruptive innovation and early-stage investments in frontier platform technologies, while building a collaborative network of innovative resources [1] Group 2 - The fund aims to leverage fiscal funds to stimulate investment and ecological cooperation with more excellent sub-funds and projects [1] - The initiative supports the construction of Shanghai as an international science and technology innovation center, injecting strong momentum into the future industrial development of Shanghai [1]

Core Insights - Shanghai Future Industry Fund has successfully completed an expansion, increasing its scale from 10 billion to 15 billion yuan, with 8 billion yuan already paid in [1] - The fund has invested in cutting-edge fields such as controllable nuclear fusion, quantum computing, AI for science, and brain-computer interfaces [1] - The fund aims to focus on disruptive innovation and early-stage investments in frontier platform technologies, while collaborating with the Shanghai Future Qidian community to build an innovative resource synergy network [1] - The initiative is designed to leverage fiscal funds to stimulate investment and ecological cooperation with more excellent sub-funds and projects, contributing to the construction of Shanghai as an international science and technology innovation center [1]

Core Insights - Nvidia's founder Jensen Huang announced a $5 billion investment in Intel, marking a significant collaboration between the two companies after decades of rivalry in the chip industry [1] - This partnership aims to develop the revolutionary "Intel x86 with RTX" chip, which could reshape the semiconductor landscape [1] - The historical context of Nvidia and Intel's competition highlights the evolution of the chip industry and the potential for major shifts in market dynamics [1] Historical Context - In 1992, Jensen Huang and his co-founders recognized the growing demand for graphics processing, leading to the establishment of Nvidia [2][3] - Nvidia's early struggles were contrasted with Intel's dominance in the CPU market, which held over 80% market share in the early 1990s [3] - Despite initial indifference, Intel allowed Nvidia to find its footing in the market, leading to the launch of the NV1 chip in 1995 [4] Competitive Dynamics - Nvidia's introduction of the GeForce 256 in 1999 marked its rise in the GPU market, while Intel remained focused on CPUs [5] - The relationship began to sour as Nvidia challenged Intel's chipset business with its nForce chipset in 2001, leading to legal disputes [6][8] - Nvidia's strategic shift towards collaboration with AMD and increased patent control followed its legal battles with Intel [8] Market Evolution - By 2010, Nvidia had established a stronghold in the discrete GPU market, while Intel struggled with its Larrabee project aimed at competing in the GPU space [9][10] - Nvidia's CUDA architecture revolutionized computing by enabling parallel processing, positioning it as a leader in the GPU market [12][13] - The emergence of AI in 2012 further solidified Nvidia's dominance, as its GPUs became essential for deep learning applications [16] Manufacturing Strategies - Intel's manufacturing model faced challenges with delays in its 10nm process, while Nvidia adopted a fabless model, outsourcing production to TSMC [18][19] - This strategic choice allowed Nvidia to focus on innovation and design, while Intel's manufacturing setbacks contributed to its decline [19] Current Landscape - The partnership between Nvidia and Intel represents a significant shift in the semiconductor industry, as both companies seek to adapt to changing market conditions [20][21] - However, the competitive landscape has evolved, with AMD gaining market share and specialized chips emerging as alternatives to traditional GPUs [22][23] - Geopolitical factors also play a crucial role in shaping the future of the semiconductor industry, impacting both companies' strategies [24][26] Conclusion - The collaboration between Nvidia and Intel signifies a new chapter in their long-standing rivalry, but the future remains uncertain as the industry continues to evolve [24][26]

Group 1 - The core point of the article is the announcement of the termination of Tesla's "Dojo Supercomputer Project," which was once considered a significant initiative in AI training but ultimately failed after five years of operation [1][3] - Elon Musk had previously expressed confidence in the project, claiming it would achieve "computing supremacy" by 2026, highlighting the abruptness of the project's closure [3][5] - The project was led by Peter Bannon, a key figure recruited from Apple, who has since left to start a new venture [1][3] Group 2 - Tesla has raised approximately $17.6 billion and generated over $60 billion in total revenue, with a peak market value of $1.3 trillion [3][5] - SpaceX, another Musk venture, has an estimated investment of $20 billion to $30 billion and is projected to generate over $10 billion in revenue from subscription services by 2025 [5][6] - Despite high revenues, both Tesla and SpaceX have faced challenges in profitability, with Tesla's net profit significantly lower than that of competitors like TSMC and BYD [5][6] Group 3 - The Dojo supercomputer was designed to train Tesla's Full Self-Driving (FSD) system, utilizing a high-performance D1 chip that offers 3 to 4 times the computing power of NVIDIA's A100 chip [20][22] - The Dojo system was intended to achieve an astonishing computing capability of 100 Exa-FLOPS, but faced significant delays and compatibility issues due to its unique architecture [20][22] - Musk's decision to halt the project reflects a strategic pivot, as he has begun procuring NVIDIA H100 chips and collaborating with TSMC and Samsung for alternative AI solutions [24][25] Group 4 - The failure of the Dojo project is attributed to high costs and a significant gap between investment and returns, compounded by Musk's expansive business ambitions [25][27] - Musk's focus on cost management has led to innovative strategies in battery production and rocket manufacturing, but the same approach has created challenges in the AI sector [27][30] - The competitive landscape in AI has intensified, with Musk acknowledging the need for alternative solutions as Tesla has shifted 70% of its training tasks back to cloud platforms like AWS and Google Cloud [41][43]

Core Viewpoint - The article emphasizes the need to reconstruct the technology service framework to bridge the gap between innovation and industry, addressing the challenges posed by rapid technological breakthroughs and traditional service limitations [1][4][14]. Group 1: Challenges in Future Industry Development - Future industries face three main challenges: technological ambiguity, ownership dilemmas, and capital gaps [3]. - Disruptive innovations often break traditional technological evolution paths, leading to non-linear and explosive advancements, creating a technological fog [3]. - Breakthroughs in future industries typically arise from interdisciplinary collaboration, complicating ownership determination due to fragmented contributions [3]. - Early validation of disruptive technologies requires long-term capital support, but the risk-averse nature of financial systems creates a capital gap [3]. Group 2: Reconstructing Technology Service Framework - The Shanghai Technology Exchange (STE) is redefining its role from a transaction facilitator to an ecosystem builder, focusing on risk-sharing and standard-setting [4][5]. - STE is developing a technology assessment system and industry mapping to enhance strategic planning capabilities and support the transformation of research outcomes into market applications [5][6]. Group 3: Comprehensive Mechanism for Technology Transfer - STE is establishing a comprehensive mechanism from identification to transformation, addressing the challenges of identifying and converting future industries [6]. - A precise identification system has been created, integrating policy, talent, industry, and technology maps to predict technology maturity [6][7]. - STE has pioneered a dynamic segmentation mechanism for rights confirmation based on R&D milestones, creating a complete closed-loop system for rights registration and technology maturity assessment [7][8]. Group 4: Innovation in Financial Support - STE is innovating financial models to create a value-sharing system, transitioning from simple credit support to long-term value sharing [11][12]. - The STE has facilitated 1,673 projects in the biopharmaceutical sector, with a total transaction amount of 28.839 billion yuan, demonstrating its role in enhancing financing options for innovative enterprises [11]. Group 5: Building a Vibrant Technology Service Ecosystem - STE is enhancing the infrastructure for technology factor markets, exploring new financial tools like technology asset securitization and intellectual property insurance [13]. - The STE aims to integrate China's innovation ecosystem into the global landscape, promoting collaboration in capital, incubation, policy, and technology [14].