Investment Rating - The investment rating for the company is "Outperform" [6][30]. Core Insights - The company's Q2 performance exceeded expectations, driven by strong retail growth, with revenue of $167.7 billion, a year-on-year increase of 13% [10]. - Advertising revenue grew by 22% year-on-year, primarily driven by sponsored products, contributing to improved profit margins [2][16]. - The cloud business (AWS) continued its growth momentum with revenue of $30.9 billion, a year-on-year increase of 17.5%, despite facing supply constraints [3][19]. Summary by Sections Overall Performance - Q2 revenue reached $167.7 billion, surpassing company guidance and Bloomberg consensus expectations of 9.6% growth, with operating profit of $19.2 billion, up 31% year-on-year [10]. - The company expects Q3 revenue to be between $174 billion and $179.5 billion, reflecting a year-on-year growth of 10%-11% [10]. Retail and Other Businesses - Retail and other business revenue was $136.8 billion, a year-on-year increase of 12%, with advertising revenue contributing significantly [2][16]. - The operating profit margin for retail and other businesses reached 6.6%, up 2.2 percentage points year-on-year, due to improved logistics efficiency [2][16]. Cloud Business - AWS revenue was $30.9 billion, a year-on-year increase of 17.5%, with an operating profit margin of 32.9% [3][19]. - The company is experiencing supply constraints due to chip shortages and delivery delays, which are expected to persist in the coming quarters [3][19]. Financial Forecasts - Revenue forecasts for 2025-2027 have been slightly adjusted to $706.3 billion, $776.9 billion, and $856.2 billion, respectively [30]. - Net profit forecasts for the same period have been slightly reduced to $70.9 billion, $82.6 billion, and $99.0 billion, respectively [30]. Key Financial Metrics - The company is projected to achieve an EPS of $6.70 in 2025, with a PE ratio of 32 [5][32]. - The operating margin is expected to improve to 11% by 2026, with a net profit growth rate of 20% in 2025 [5][32].

Core Viewpoint - Amazon's Q2 results exceeded market expectations in both revenue and adjusted EPS, indicating strong operational performance and growth potential despite some concerns regarding operating income guidance for Q3 [3][4][5]. Financial Performance - Q2 revenue reached $167.7 billion, surpassing the expected $162.1 billion by 3% [3][4]. - Adjusted EPS was $1.68, exceeding the forecast of $1.33 by over 20% [3][4]. - Q3 revenue guidance midpoint is projected at $176.75 billion, which is $3.5 billion higher than market expectations [4]. - AWS segment sales grew 17.5% year-over-year to $30.9 billion, while North America segment sales increased 11% year-over-year to $100.1 billion [4][5]. Operating Income Insights - Q2 operating income was $19.2 billion, a year-over-year increase of over 30% [4][5]. - Q3 operating income guidance ranges from $15.5 billion to $20.5 billion, with the midpoint falling short of market expectations [4][5]. - North America operating margin reached 7.5%, indicating a shift towards more profitable revenue streams [5][6]. Segment Performance - North America segment net sales were $100.1 billion, with a year-over-year growth of 11% [6]. - International segment net sales were $36.8 billion, also showing a year-over-year growth of 11% [6]. - AWS segment net sales were $30.9 billion, maintaining a strong growth trajectory [6]. Innovation and Future Prospects - Amazon is focusing on enhancing operational efficiency through innovations like the Vulcan robot, which has tactile capabilities [7][10]. - The company is expanding its Prime membership offerings and enhancing its logistics capabilities [8][10]. - The introduction of generative AI tools and partnerships indicates a commitment to leveraging technology for future growth [8][10]. Valuation Metrics - Amazon's current valuation metrics, including P/E ratios and EV/EBITDA, are significantly below historical averages, suggesting potential for future price appreciation [11][12]. - The expected P/E ratio is projected to be around 35, which is considered reasonable given the anticipated growth in net profits [12][13]. Market Position and Challenges - Despite strong fundamentals, Amazon faces competitive pressures in e-commerce and cloud computing from companies like MercadoLibre and Microsoft [10][13]. - Regulatory concerns may arise due to Amazon's size and market influence, which could impact future operations [10][13].

Core Viewpoint - Amazon's Q2 earnings report reveals a mixed performance, with strong revenue but significant concerns over AWS's growth and profitability, particularly in the context of AI demand outpacing supply and rising operational costs [1][2][5][6]. Financial Performance - Amazon's total revenue for Q2 reached $167.7 billion, a 12% year-over-year increase when excluding foreign exchange impacts [27]. - AWS generated $30.9 billion in sales, reflecting a 17.5% year-over-year growth, but this growth is seen as insufficient compared to competitors [1][30]. - AWS's operating profit margin fell sharply from 39.5% in Q1 to 32.9% in Q2, primarily due to increased capital expenditures for AI support [2][31]. AI and Supply Constraints - CEO Andy Jassy acknowledged a significant supply constraint in AI capabilities, stating that demand currently exceeds supply, with electricity being the primary limiting factor [5][6][41]. - The company is investing heavily in AI infrastructure, including the development of its proprietary AI chip, Trainium2, which is claimed to be 30% to 40% more cost-effective than competitors' GPUs [3][8][22]. Competitive Landscape - Despite AWS's strong position, concerns are growing about its ability to maintain market leadership as competitors achieve higher growth rates [1][30]. - Jassy emphasized AWS's advantages in security and operational performance, attempting to reassure investors about its competitive edge [2][8][37]. Other Business Segments - Amazon's retail business performed well, with record sales during Prime Day and a 22% year-over-year growth in advertising revenue [3][7][30]. - However, Jassy expressed caution regarding potential impacts from tariffs, indicating uncertainty about future demand and pricing [4][7][18]. Future Outlook - The company plans to continue investing in AI and cloud infrastructure to meet growing demand, with expectations of gradual improvements in supply constraints over the coming quarters [31][41]. - Amazon's Project Kuiper aims to address the digital divide by providing broadband access to underserved areas, indicating a long-term growth strategy beyond its core e-commerce and cloud services [47].

CoreWeave Overview - CoreWeave provides specialized GPU-accelerated infrastructure for AI through 33 data centers with 420 megawatts of active power across the US and Europe [2] - The company announced a $6 billion investment for a new data center in Lancaster, PA, with an initial capacity of 100 megawatts, scalable to 300 megawatts [2] - CoreWeave has a revenue backlog of $259 billion, including a significant $11.9 billion deal with OpenAI and a $4 billion expansion agreement with a major AI client [5][9] Amazon Overview - Amazon's AWS is a market leader in cloud computing and is aggressively expanding into AI infrastructure, launching custom AI chips and strengthening partnerships with companies like NVIDIA [9][12] - AWS revenues grew 17% year over year in Q1 2025, with an annualized revenue run rate of $117 billion and a backlog of $189 billion [10][11] - Amazon's AI business operates at a multi-billion-dollar annual revenue run rate with triple-digit percentage growth year over year [12] Market Position and Performance - CoreWeave is positioned to benefit from the AI infrastructure boom, with a forecasted global economic impact of AI reaching $20 trillion by 2030 and a total addressable market of $400 billion by 2028 [4] - Amazon's AWS is well-poised to benefit from AI demand at scale, with significant investments in generative AI and custom silicon development [11][12] - Over the past month, AMZN shares gained 6.9%, while CRWV stock declined by 24.1% [15] Financial Metrics and Valuation - CoreWeave's stock is trading at a Price/Book ratio of 30.22X, while Amazon's is at 8.06X, indicating that both companies are considered overvalued [19][17] - Analysts have kept earnings estimates unchanged for CoreWeave, while there has been a marginal upward revision for Amazon [20][22] Investment Outlook - Amazon is viewed as a more stable and diversified investment in AI cloud infrastructure, with AWS as a high-growth engine [22] - CoreWeave, while specialized in AI infrastructure, faces execution risks due to high capital expenditures and customer concentration, with 77% of its 2024 revenue coming from its top two clients [8][9]

Core Insights - Amazon Web Services (AWS) has officially dissolved its Shanghai AI Research Institute, marking the closure of its last overseas research facility [1][2] - The decision to downsize certain teams is part of a broader strategic realignment aimed at optimizing resources and continuing investment in innovation [1][2] Group 1: Background and Establishment - The Shanghai AI Research Institute was established in the fall of 2018, focusing on four main areas: open-source project development, foundational research in graph neural networks (GNNs), empowering clients with AI technology, and collaborating with academic institutions [2][3] - The institute achieved notable successes in the neural network field, with the DeepGraphLibrary (DGL) framework becoming a globally recognized open-source project [3] Group 2: Market Dynamics and Competition - The closure of the Shanghai AI Research Institute reflects a trend among foreign enterprises in China facing deep adjustments due to intensified local competition from domestic tech companies like Huawei, Alibaba, and Tencent [3][4] - The global economic landscape has prompted companies to reassess their investment strategies, focusing on core business areas and reallocating overseas research resources [4] Group 3: Strategic Intentions - AWS's decision to close its last overseas research institute indicates a strategic shift towards prioritizing investments in generative AI and other cutting-edge fields that promise more immediate commercial returns [5][7] - The competitive landscape in cloud computing and AI is becoming increasingly fierce, with AWS facing challenges from Microsoft Azure and Google Cloud, as well as local players [6][7] Group 4: Future Directions - AWS plans to invest up to $100 billion by 2025, primarily in AI-related projects, including data centers and AI hardware, to enhance its market position [6] - The company is focusing on balancing innovation with cost control while ensuring that core business capabilities remain unaffected amid team downsizing [7]

Core Insights - The core challenge for enterprises in AI deployment is transforming technological potential into real productivity despite significant investments in AI exploration [1][10] - Amazon Web Services (AWS) has introduced Amazon Bedrock AgentCore, a comprehensive intelligent agent system aimed at addressing the current limitations in enterprise AI deployment [3][5] Group 1: AI Deployment Challenges - Many enterprises struggle with large-scale AI deployment due to infrastructure limitations, security concerns, and operational complexities [1][4] - Typical issues include authorization for AI operations, compatibility of identity authentication systems, and the management of multi-turn dialogues [4][5] Group 2: Amazon Bedrock AgentCore Features - Amazon Bedrock AgentCore consists of seven core modules designed to facilitate agent construction, operation, invocation, memory, interaction, and governance [4][5] - Key features include AgentCore Runtime for extended task execution, AgentCore Identity for granular permission control, and AgentCore Browser Tool for cloud-based web operations [4][5] Group 3: Cost and Efficiency Improvements - The introduction of Amazon S3 Vectors significantly reduces vector processing costs by 90%, enabling agents to retain more business context and improve reasoning capabilities [6][7] - The Amazon Nova model customization service allows businesses to inject proprietary knowledge into models, enhancing decision-making accuracy and content credibility [7] Group 4: Marketplace and Ecosystem Development - AWS has launched a new "AI Agents and Tools" category in its Marketplace, allowing users to easily browse, procure, and deploy various agents and tools [8] - The new IDE tool Kiro integrates agents into the entire development lifecycle, enhancing efficiency and positioning agents as organizational-level AI assistants [9] Group 5: Strategic Business Implications - AWS's design principles emphasize agile response, foundational restructuring, data collaboration, and delivery orientation, indicating a shift in how software is constructed and deployed [10] - Gartner predicts that by 2027, over half of Chief Data and Analytics Officers will secure dedicated budgets for data literacy and AI literacy projects, reflecting a significant shift in investment priorities [10]

Core Insights - The article discusses the rapid evolution and changing landscape of the large model industry, highlighting a shift from numerous players to a few dominant ones focusing on capital and technology battles [2][29] - The focus has transitioned from model performance to the practical application of large models in business productivity, with "Agent" technology emerging as a key solution [4][8] Group 1: Industry Trends - The "hundred model battle" of 2023 has evolved into a scenario where the market is dominated by a few players, emphasizing the importance of converting large model capabilities into business value [2][29] - The emergence of Agentic AI is driven by advancements in agent orchestration frameworks and standardized protocols, making it easier to build and deploy agents across various industries [10][19] Group 2: Agentic AI Development - AWS's recent summit emphasized Agentic AI as a transformative technology that allows large models to take proactive actions rather than just responding to prompts [8][10] - The article outlines six key challenges that need to be addressed for agents to transition from proof of concept to production, including security, memory management, and tool discovery [12][13] Group 3: Amazon Bedrock AgentCore - AWS introduced Amazon Bedrock AgentCore to lower the barriers for building enterprise-level agents, providing a comprehensive solution that includes runtime environments, memory systems, and identity management [15][19] - The AgentCore framework allows developers to deploy agents without needing extensive knowledge of cloud-native environments, thus facilitating faster and safer deployment [15][19] Group 4: Customization and Advanced Features - For enterprises with specific needs, AWS offers advanced features like S3 Vectors for efficient vector storage and retrieval, and Amazon Nova for model customization [21][25] - The introduction of Kiro, an AI IDE product, aims to enhance coding efficiency by integrating product requirements and documentation into the development process [26]

Core Insights - AWS has experienced significant growth in AI and cloud migration, with many customers rapidly adopting new technologies and moving their entire business systems to the cloud [4][6] - The company anticipates that the proportion of inference workloads in AI will continue to rise, with predictions that 80% to 90% of AI workloads will be inference-based in the long term [5][8] - AWS's AI business has reached a multi-billion dollar scale, driven by customer usage of AWS and internal applications of generative AI technology [6][7] AWS Achievements - AWS has seen remarkable customer innovation and technology adoption over the past year, particularly in the context of AI and generative technologies [4] - The launch of the "European Sovereign Cloud" is expected to create significant market opportunities, addressing customer concerns about data sovereignty [5] AI Workloads and Inference - The shift from training to inference in AI workloads is evident, with inference now surpassing training in usage [10] - AI is becoming an integral part of application development and user experience, making it difficult to quantify the revenue generated by AI-driven applications [9] Industry Indicators and Innovations - Token generation is recognized as a relevant metric, but it is not the sole measure of AI workload, as many models perform extensive computations before generating outputs [11] - Project Rainier, a collaboration with Anthropic, aims to create a massive computing cluster for training next-generation cloud models, showcasing AWS's commitment to innovation [13] Open Ecosystem and Collaboration - AWS emphasizes the importance of providing customers with a variety of technology options, avoiding a binary competition narrative with Nvidia [14][15] - The company is expanding its data center capacity in Latin America, with new regions in Mexico and Chile to meet growing customer demand [18]

Core Insights - AWS has achieved significant growth in AI and cloud migration, with a notable increase in customer adoption of new technologies and innovations [3][4] - The AI business has reached a multi-billion dollar scale, with AWS contributing significantly through its infrastructure and services [4][5] - The shift towards AI-driven applications is expected to reshape business operations across industries, marking the beginning of a transformative era [4][6] AWS Achievements - AWS has experienced a year of remarkable innovation, particularly in customer-driven AI technology adoption [3] - The company has seen a surge in clients migrating their entire business systems to the cloud, driven by advancements in AI and generative technologies [3][4] AI Business Scale - AWS's AI business has reached a multi-billion dollar scale, with contributions from both its infrastructure services and internal applications [4][5] - The AI technology is being utilized across various aspects of Amazon's operations, enhancing logistics, customer interactions, and product discovery [5] Rise of Inference Economy - The proportion of AI workloads focused on inference is expected to increase significantly, with predictions that 80% to 90% of AI workloads will be inference-based in the long term [6][7] - Inference is becoming an essential component of applications, integrating deeply into user experiences [7][8] Industry Metrics and Innovations - Token generation is emerging as a relevant metric for measuring AI performance, although it has limitations in reflecting actual workload [9][10] - The industry is witnessing a shift in how token metrics are perceived, with a growing recognition of the complexity of AI tasks beyond simple token counts [9][10] Project Rainier - Project Rainier, a collaboration with Anthropic, aims to create a massive computing cluster for training next-generation cloud models, showcasing AWS's commitment to AI advancements [10][11] - The deployment of Tranium Two servers is underway, with promising performance metrics being reported [10][11] Open Ecosystem and Collaboration Strategy - AWS emphasizes the importance of providing customers with diverse technology options, avoiding a binary competition narrative with Nvidia [14][15] - The company is actively expanding its partnerships and ensuring compatibility with various platforms to meet customer needs [17][18] Data Center Expansion - AWS is expanding its data center capacity in Latin America and Europe, with a focus on the upcoming "European Sovereign Cloud" to address data sovereignty concerns [19][20] - The company is committed to enhancing its infrastructure to support growing customer demands across different regions [19][20]

[Music] Um, yeah. So, my name is Mike Chambers. I'm going to pick you up a little bit there. So, I'm from Queensland in the eastern part of Australia, but that's okay. Um, yeah, very happy to be here. So, I'm a developer advocate for Amazon Web Services. Um, and I completely and utterly and only and totally spe specialize in generative AI. Used to be machine learning. Now it's generative AI. Um, I'll be talking about why this slide is up here in a moment. Any tabletop RPG players in the room? There's got to ...