J P M O R G A N North America Equity Research 12 December 2025 Communications Infrastructure 2026 Outlook: Crucial Year for Hyperscale AI Capacity Delivery as AI Infrastructure Needs Evolve; Towers Poised for Growth, but EchoStar Uncertainty Remains The data center industry went into overdrive in 2025, with incremental capacity builds doubling from last year, and we look for even more supply to be brought online in 2026. This year, AI-focused companies have announced a wave of deals totaling tens of billion ...

AWS kicked off re:Invent 2025 in Las Vegas on Tuesday (Dec. 2) with high expectations. As the artificial intelligence (AI) race heats up, Amazon needs to prove that its years of heavy investment in model infrastructure and automated systems are paying off. The company is going up against Microsoft and Google, both of which are rapidly expanding their cloud AI services. By completing this form, you agree to receive marketing communications from PYMNTS and to the sharing of your information with our sponsor, ...

Core Insights - Amazon Web Services (AWS) showcased an unprecedented number of product launches at the re:Invent 2025 event, with CEO Matt Garman challenging himself to release 25 products in 10 minutes, ultimately unveiling 40 new products in just over two hours, emphasizing practicality and addressing challenges in AI applications [1][7][9]. Group 1: AI Computing Power - AWS has restructured its AI computing supply model by focusing on self-developed chips, specifically the Trainium series, which has grown into a multi-billion dollar business with over 1 million chips deployed, outperforming competitors by four times in speed [15][20]. - The latest Trainium3 Ultra Servers, based on 3nm technology, offer a 4.4 times increase in computing performance and a 3.9 times increase in memory bandwidth compared to the previous generation [18]. - The upcoming Trainium4 chip promises significant advancements, including a 6 times increase in FP4 computing performance and a 4 times increase in memory bandwidth, tailored for large model training needs [20][22]. - AWS introduced AI Factories, allowing clients to deploy AWS AI infrastructure within their data centers, thus maintaining control and security while accessing top-tier AI computing power [23][24]. Group 2: Model Development and Integration - AWS launched Amazon Bedrock, a flexible and customizable model platform, which now includes Chinese models Kimi and MiniMax, marking their entry into the global developer ecosystem [26][28]. - The new Amazon Nova 2 series includes various models designed for different tasks, with Nova 2 Light focusing on cost-effectiveness and low latency, Nova 2 Pro excelling in complex tasks, and Nova 2 Sonic optimizing real-time voice interactions [30][32]. - Nova Forge introduces the concept of Open Training Models, allowing enterprises to integrate their proprietary data with AWS's training datasets, creating specialized models that retain general reasoning capabilities while understanding unique business knowledge [40][41]. Group 3: AI Agents - AI Agents emerged as a key focus, with Garman stating that the era of AI assistants is being replaced by AI Agents, which will be widely adopted across companies [45][46]. - AWS introduced several new Agents, including Kiro Autonomous Agent for complex development tasks, AWS Security Agent for proactive security measures, and AWS DevOps Agent for continuous system monitoring and troubleshooting [50][52][56]. - AWS provides tools like AWS Transform Custom for code migration and Policy in AgentCore for defining agent behavior, ensuring that agents operate within controlled parameters [58][61]. Group 4: Strategic Vision - AWS's strategy emphasizes the importance of practical applications of AI technologies, focusing on building a comprehensive, secure, and scalable enterprise-level infrastructure rather than solely on technological breakthroughs [68][70]. - The company aims to address challenges related to computing costs, model understanding of proprietary knowledge, and the controllability of AI Agents through its innovative solutions and partnerships [70].

Core Insights - Applied Digital has signed a 15-year lease agreement for 200 MW of IT capacity at the Polaris Forge 2 Campus, generating approximately $5 billion in total contracted revenue [1] - The total leased capacity across Polaris Forge 1 and Polaris Forge 2 has now reached 600 MW, positioning the company as a leading builder of AI infrastructure in the U.S. [2] Lease Agreement Details - The lease is with a U.S.-based investment-grade hyperscaler and is designed to support AI and high-performance computing infrastructure [1] - The hyperscaler has a first right of refusal for an additional 800 MW, indicating potential future expansion [1] Campus Specifications - Polaris Forge 2 spans over 900 acres and is engineered for efficiency with a projected Power Usage Effectiveness (PUE) of 1.18 and near-zero water consumption [3] - The initial 200 MW will be phased in two buildings, expected to come online in 2026 and reach full capacity by 2027 [3] Company Achievements - The announcement follows record growth, including a 150 MW lease with CoreWeave and a $5 billion partnership with Macquarie Asset Management [4] - Applied Digital was recognized as the top company in the Dallas Business Journal's Fast 50, highlighting its rapid expansion in digital infrastructure [4] Strategic Vision - The company emphasizes its ability to deliver large-scale data centers quickly and efficiently, reshaping the AI infrastructure landscape [3] - The CEO stated that the company's AI Factories are redefining hyperscale infrastructure development, focusing on responsible and rapid construction [5]

Core Insights - SOPHiA GENETICS has expanded its partnership with AstraZeneca to enhance data-driven medicine for breast cancer treatment [1][3] - The collaboration will utilize SOPHiA GENETICS's AI Factories to analyze multimodal healthcare data and generate insights for optimizing treatment outcomes [2][3] Company Overview - SOPHiA GENETICS is a cloud-native healthcare technology company focused on data-driven medicine, particularly in cancer and rare disorders [5] - The company offers the SOPHiA DDM™ Platform, which analyzes complex genomic and multimodal data to provide actionable insights [5] Partnership Details - The multi-year collaboration aims to develop a bespoke AI-powered predictive model for breast cancer treatment [1][2] - AstraZeneca will leverage SOPHiA GENETICS's AI capabilities to generate real-world evidence and enhance clinical decision-making [2][3] Strategic Importance - This partnership highlights the increasing demand for secure and scalable AI applications in healthcare [3] - The collaboration reinforces SOPHiA GENETICS' position as a trusted technology partner in advancing global health through federated data analytics [3]

Group 1 - Nvidia introduced Blackwell Ultra, AI Factories, and Dynamo at GTC 2025 to strengthen its position in the AI market [1] - These new products offer high performance and scalability but are accompanied by rising prices, power constraints, and competitive threats [1] - The emergence of hyperscalers developing their own AI processors poses a challenge for Nvidia [1] Group 2 - Pythia Research focuses on identifying multi-bagger stocks, particularly in the technology sector, using a multidisciplinary approach [1] - The strategy combines financial analysis, behavioral finance, psychology, social sciences, and alternative metrics to find companies with high conviction and asymmetric risk-reward potential [1] - The aim is to uncover breakout opportunities before they gain mainstream attention, navigating market sentiment and identifying emerging trends [1]