今天，我们就会从这些维度，带你拨开数据的表面，看到背后真正的逻辑。本次分析，将是全网独一无二的深度解读。如果你想领先市场一步，千万不要 错过任何一个细节。 英伟达未来三大催化剂 英伟达如今的市值已经飙到 4.34 万亿美元（截止上周五），比日本一整年的GDP还要高。 英伟达之所以这么牛绝不仅仅因为GPU卖得好，那只是表层的故事。真正让资本市场疯狂的是，它数次财报里透露出来的对未来AI时代垄断地位的巨大 预期。 我们美股投资网是唯一敢在英伟达财报前，明确亮明自己观点的频道！从2024年2月19日至今，我们已经连续做了六次英伟达财报前瞻，其中 5次全部正 确。 这一次我们也参考了大量的资料，力求用数据说话！ 我们这次对英伟达财报判断是：大概率超预期。但重点在于，英伟达的股价已经提前消化了大量利好，想要在这个位置来一波大涨，难度比之前可要大得 多。换句话说，涨没问题，但不期望会暴涨。 曾成功投资过脸书推特Robinhood和Coinbase的美国顶级的风险投资（a16z）表示过，英伟达的优势，并非只是GPU性能，还有其围绕芯片，在网络、内 存、供应链及产业生态上建立的护城河。 问题是，资本市场的逻辑残酷——没有永远 ...

据英伟达介绍，Cosmos Reason赋予机器人和AI代理"推理"能力，凭借其记忆与物理理解能力，可"作 为规划模型推测具身智能体下一步可能采取的行动"。它可应用于数据整理、机器人规划及视频分析等 领域。 例如，运行该模型的机器人手臂可以根据"面包+烤面包机"的场景，推断出将面包放进烤面包机进行烘 烤是最合理的下一步动作，并将思考逻辑转化为操作指令。 Cosmos Reason在机器人及物理AI领域拥有多种应用场景。其数据整理与标注功能，可以帮助开发者自 动化完成对海量且多样化训练数据集的筛选、评估与标注，大幅提升数据处理效率。 周一，英伟达(NVDA.O)发布了一套面向机器人开发者的新一代全球AI模型、库及其他基础设施，其中 最引人注目的是"Cosmos Reason"，一款拥有70亿参数、面向物理AI应用与机器人的"推理型"视觉语言 模型。 此次加入现有Cosmos世界模型阵列的还包括Cosmos Transfer-2，可加速从3D仿真场景或空间控制输入 生成合成数据，以及一款为速度优化的精简版Cosmos Transfer。 英伟达在周一SIGGRAPH大会上表示，这些模型旨在用于创建合成文本、图像和 ...

Core Insights - Marvell Technology is advancing its semiconductor technology by transitioning to 2nm and below nodes, utilizing innovative techniques such as gate-all-around transistors and backside power delivery [2] - The company is leveraging modular redistribution layer (RDL) technology to enhance its 2.5D packaging solutions, which can integrate multiple chips and improve power efficiency while reducing costs [2] - Marvell's potential market for data center semiconductors is projected to reach $94 billion by 2028, with a compound annual growth rate (CAGR) of 53% for its custom computing products from 2023 to 2028 [3] Marvell Technology's Innovations - Marvell is utilizing advanced packaging solutions, including 2.5D designs, to develop multi-chip AI accelerator solutions that are 2.8 times larger than existing single-chip solutions [2] - The RDL technology allows for shorter interconnect distances, reducing latency and improving power efficiency, while also enabling seamless replacement of defective chips [2] Competitive Landscape - Broadcom's AI semiconductor revenue is expected to reach $5.1 billion in Q3 FY2025, driven by a 46% year-over-year increase in AI revenue, particularly in AI networking [4][6] - Broadcom's next-generation Tomahawk 6 Ethernet switch, designed for AI-scale architectures, features a transmission rate of up to 102.4 Tbps, addressing network bottlenecks in high-performance AI systems [5] - NVIDIA continues to dominate the AI semiconductor space with its unparalleled GPU performance and scalable AI deployment solutions [6] Industry Trends - The rapid growth in data center infrastructure investments is benefiting companies like Marvell Technology, which is positioned to capitalize on the increasing demand for advanced semiconductor solutions [3] - Intel is advancing its AI strategy with a roadmap aimed at achieving process leadership by 2025, focusing on efficient server chips for high-density AI tasks [6]

Core Insights - Broadcom is experiencing significant growth in AI revenues, reporting a 46% year-over-year increase to $4.4 billion in Q2 of fiscal 2025, with AI networking revenues surging over 170% [1][10] - The company anticipates AI semiconductor revenues to reach $5.1 billion in Q3 of fiscal 2025, indicating a potential 60% year-over-year growth [2][10] - Broadcom's Ethernet-based networking portfolio, including Tomahawk switches and Jericho routers, is widely adopted by major hyperscalers like Google, Meta, and Microsoft, highlighting the importance of networking in AI workloads [3] AI Technology and Innovations - The launch of the next-generation Tomahawk 6 Ethernet switch, capable of 102.4 Tbps, aims to address networking bottlenecks in high-performance AI systems [4][10] - Innovations such as Cognitive Routing 2.0 and co-packaged optics are designed to enhance AI-scale fabrics, further solidifying Broadcom's position in the AI market [4] Competitive Landscape - NVIDIA remains a dominant player in the AI semiconductor market, offering high-performance GPUs and cloud solutions that drive scalable AI deployment [6] - Intel is advancing its AI strategy with new CPU and GPU architectures aimed at edge and data center workloads, indicating increased competition in the AI semiconductor space [7] Financial Performance and Valuation - Broadcom's stock has returned 18.8% year-to-date, outperforming the Zacks Electronics - Semiconductors industry, which grew by 15% [8] - The company is currently trading at a forward price-to-sales ratio of 18.11X, significantly higher than the industry average of 8.72X, suggesting potential overvaluation [11] - The Zacks Consensus Estimate for Q3 fiscal 2025 earnings is $1.66 per share, reflecting a 33.87% year-over-year growth [14]

Group 1 - Dylan Patel analyzes the recent acquisition of Scale AI by Meta, suggesting that the focus is on Alexandr Wang and his team rather than the data labeling business itself [1][17] - The acquisition signifies a strategic shift for Meta, moving from a cautious approach to aggressively pursuing "superintelligence" due to perceived lag in AI advancements [1][19] - Patel believes that the AI landscape is evolving, with companies like OpenAI leading the charge, while Meta is positioned to attract top talent to remain competitive [3][23] Group 2 - Apple faces challenges in attracting top AI researchers due to its corporate culture, compensation, and lack of computational resources compared to competitors like Anthropic and Meta [2][56] - The company has historically made small acquisitions and struggles to create an appealing environment for AI talent, which hinders its competitive edge [51][56] - Patel expresses skepticism about the future of edge AI, suggesting that consumer preference for free cloud-based services will limit the adoption of device-side AI [62][63] Group 3 - Nvidia has built a strong moat with its hardware and software ecosystem but faces backlash from cloud service providers due to its recent acquisition of Lepton and the launch of DGX Cloud [2][10] - Patel criticizes Nvidia's strategy as a significant error, as it directly competes with cloud service providers, leading to potential shifts towards AMD [2][10] - The future of AI work automation is predicted to be slower than many expect, with significant automation unlikely to occur until the end of the decade [10][36] Group 4 - The relationship between Microsoft and OpenAI is described as tumultuous, with concerns over IP control and profit-sharing agreements creating uncertainty for OpenAI's future [27][30] - Patel highlights the complexities of the deal structure between Microsoft and OpenAI, emphasizing the potential risks for OpenAI's developers regarding IP ownership and profit distribution [30][36] - The ongoing competition for "superintelligence" is expected to intensify, with OpenAI currently leading and Meta positioned to catch up [3][23]

Summary of Key Points from Conference Call Records Industry or Company Involved - **MU (Micron Technology)**: Earnings report expectations - **RDDT (Reddit)**: Advertising strategy and revenue potential - **NVDA (Nvidia)**: AI demand and market cap projections - **COIN (Coinbase)**: Market position and revenue forecasts - **MSFT (Microsoft)**: AI adoption and growth potential - **AMZN (Amazon)**: Delivery expansion and retail margins - **NOW (ServiceNow)**: AI-driven CRM opportunities - **DUOL (Duolingo)**: Growth in EdTech - **IOT (Samsara)**: Automation and asset monitoring demand - **TSLA (Tesla)**: Sales performance in Europe Core Points and Arguments Micron Technology (MU) - Earnings expectations for August quarter EPS are in the range of $2.20-$2.30 [1] Reddit (RDDT) - Positive initiation from Cleveland citing revenue upside driven by product traction and improving ROI [2] - RBC estimates potential revenue upside of over $25 million in Q2 if ad load expands, currently at ~15% [3][4] Nvidia (NVDA) - Loop Capital raised price target to $250, citing massive upside in AI infrastructure demand, projecting hyperscaler spending could reach ~$2 trillion by 2028 [5][6] - Nvidia's entry into cloud computing with DGX Cloud is seen as a potential disruptor to existing tech giants [7][8] Coinbase (COIN) - Bernstein raised price target to $510, calling Coinbase the "most misunderstood" crypto stock, highlighting its dominance in U.S. spot trading and upcoming regulatory tailwinds [9] - Citizens reiterated a $400 price target, emphasizing Coinbase's role as a partner for enterprises integrating blockchain [10][11] Microsoft (MSFT) - Wedbush raised price target to $600, citing rapid AI adoption and its transformative impact on Microsoft's cloud growth [13][14] - OpenAI's CEO discussed a positive partnership with Microsoft, indicating strong collaboration [15] Amazon (AMZN) - BofA reiterated a $248 price target, highlighting plans to expand delivery services to rural areas, which is expected to boost retail margins [16] ServiceNow (NOW) - DA Davidson initiated coverage with a $1,150 price target, emphasizing the company's strong position in AI-driven CRM [17] Duolingo (DUOL) - Argus initiated coverage with a $575 price target, noting impressive growth and expansion into new educational areas [24] Samsara (IOT) - Piper reiterated an Overweight rating with a $53 price target, citing strong demand for automation and asset monitoring [22][23] Tesla (TSLA) - Tesla's new car sales in Europe fell 27.9% in May, despite overall EV sales growth in the region [29] Other Important but Possibly Overlooked Content - KeyBanc's CIO survey indicates a slowdown in IT budget growth expectations, which could negatively impact software vendors [18][19] - H.C. Wainwright initiated coverage on CoreWeave with a Neutral rating, cautioning on near-term valuation despite strong infrastructure execution [21] - Goldman Sachs highlighted the potential disruption AI could bring to advertising economics, identifying significant market opportunities [25][26] This summary encapsulates the key insights and projections from the conference call records, providing a comprehensive overview of the involved companies and industries.

Core Viewpoint - The rise of AI cloud service providers poses a significant threat to traditional cloud service giants like Amazon, Microsoft, and Google, which have relied on cloud computing as a major profit engine [1][5]. Group 1: AI Cloud Service Providers - Nvidia launched its cloud computing service, DGX Cloud, two years ago and has invested in emerging companies like CoreWeave and Lambda to compete with major cloud providers [2]. - DGX Cloud is projected to grow into a business generating over $10 billion in annual revenue, while CoreWeave is expected to reach approximately $5 billion in revenue this year [2]. - Despite the smaller scale of these AI cloud service providers compared to Amazon's $107 billion cloud revenue last year, their emergence is causing concern among established cloud giants [5]. Group 2: Impact on Traditional Cloud Giants - Amazon's cloud division contributed 29% of its revenue in the latest quarter, generating over 60% of its operating profit, highlighting its critical importance [6]. - Microsoft and Google also face significant risks; a shift in the cloud computing market could result in lost market share and strategic influence [6]. - All major cloud service providers are currently offering AI chip rental services, with Nvidia holding an estimated 80% market share in this area [6]. Group 3: Nvidia's Strategy - Nvidia's DGX Cloud operates on a unique "reverse cooperation" model, where cloud providers purchase and manage hardware, which Nvidia then rents back to them for client use [7]. - This model places traditional cloud giants in a difficult position, as they profit from Nvidia's services while also supporting a potential competitor [8]. - Nvidia has signed long-term cloud service agreements totaling $10.9 billion, a significant increase from $3.5 billion the previous year, indicating the growing scale of DGX Cloud [8]. Group 4: Future Considerations - Nvidia claims that the launch of DGX Cloud is not intended to overshadow cloud computing giants, but rather to connect customers with AI computing power and Nvidia's expertise [12]. - However, as Nvidia encroaches on the territory of cloud giants, these companies are also developing their own custom AI chips, which could threaten Nvidia's revenue [12].

公众号记得加星标⭐️，第一时间看推送不会错过。 DGX Cloud 已然快速增长。瑞银分析师在其成立之初就估计，其年收入可能超过 100 亿美元。而 CoreWeave 于 3 月份在纳斯达克上市，预计今年的收入约为 50 亿美元。 来源：内容 编译自 WSJ 。 云计算为亚马逊、微软和谷歌带来了巨额利润。如今，随着人工智能云计算专家的崛起以及行业新势 力——英伟达——的崛起，这棵摇钱树正面临新的威胁。 人工智能芯片制造商英伟达两年前推出了自己的云计算服务，名为 DGX Cloud。该公司还培育了一 批与大型云计算公司竞争的新兴企业，投资了人工智能云计算公司 CoreWeave 和 Lambda。 这些举措尚未产生巨大影响，但如果计算需求继续向人工智能转移，而英伟达仍然是该领域的主 要"军火商"，那么竞争格局的转变是可以想象的。 所有大型云计算公司实际上都在出租AI芯片，其中许多芯片由英伟达制造，英伟达的市场份额估计约 为80%。然而，这些云计算公司正在帮助英伟达发展自身的云业务，这或许也证明了英伟达的市场实 力。 这些业务受限于其对人工智能计算的狭隘关注，与亚马逊市场领先的云业务去年超过 1070 亿美元的 ...

Core Insights - Nvidia's DGX Cloud service is rapidly growing, with UBS analysts projecting annual revenue to exceed $10 billion [1] - Nvidia employs a dual strategy in the AI cloud computing sector by directly operating DGX Cloud and investing in emerging companies like CoreWeave and Lambda [2] - The DGX Cloud service allows customers to access Nvidia's AI supercomputers remotely, avoiding the need for expensive hardware purchases [3] Nvidia's Business Model - Since its launch in March 2023, DGX Cloud has expanded its partner network significantly, signing long-term cloud service agreements worth $10.9 billion, up from $3.5 billion the previous year [3] - Nvidia's unique operational model involves cloud giants purchasing and managing hardware, which Nvidia then rents back to provide services to enterprise clients [3] - This arrangement creates a complex relationship where cloud providers benefit financially while potentially aiding a competitor [5] Market Dynamics - The entry of Nvidia into the cloud computing space poses a threat to traditional giants like Amazon, Microsoft, and Google, which rely heavily on cloud services for profitability [5] - Amazon's cloud business generated over $107 billion in sales last year, contributing significantly to its overall revenue [5] - Nvidia holds approximately 80% of the AI chip market, making it a critical supplier for all major cloud service providers [5] Competitive Landscape - As Nvidia's DGX Cloud competes with existing cloud services, traditional providers are also developing their own AI chips to reduce reliance on Nvidia [5] - The shift in computing demand towards AI presents both opportunities and challenges for established cloud providers, particularly amid economic uncertainties [5]

Core Insights - Nvidia is positioned as a dominant player in the AI infrastructure market, with a projected 9% annual return, which may be a smart risk-adjusted investment in technology this decade [1][10][17] - Coatue Management estimates Nvidia's market cap could grow from $3.5 trillion to $5.6 trillion by 2030, indicating a 9.6% compound annual growth rate [2] Ecosystem and Market Position - Nvidia has established itself as the "Apple of AI," creating a robust ecosystem that includes its Compute Unified Device Architecture (CUDA) software platform, which is the default for AI development with over 4 million developers [5][6] - The company has expanded into various layers of the AI stack, offering services like DGX Cloud for renting AI supercomputers and enterprise platforms that simplify AI deployment [7][8] Financial Performance - Nvidia's data center revenue surged 73% year-over-year to $39.1 billion, with gross margins exceeding 70%, showcasing significant pricing power [11] - The company has $54 billion in cash and marketable securities, allowing it to invest aggressively while weathering market fluctuations [11] Market Expansion Potential - Nvidia is not just increasing chip sales but is also expanding the overall AI market by simplifying deployment for smaller businesses and local governments [12][13] - The potential for market growth is substantial as AI becomes accessible to a wider range of users, beyond just tech giants [13] Competitive Landscape - Nvidia trades at a forward price-to-earnings (P/E) ratio of 34, reflecting its premium valuation amid competition from companies like Advanced Micro Devices and cloud giants developing their own AI chips [14][15] - Despite challenges such as U.S. export restrictions affecting revenue from China, Nvidia's dominance and durability in the market remain strong [14][15] Long-term Outlook - Nvidia is seen as a reliable investment opportunity, offering scale, certainty, and sustained innovation, contrasting with speculative AI start-ups [17][18] - The ongoing AI revolution is expected to accelerate, further solidifying Nvidia's role in powering various technological advancements [17]