AI infrastructure

CoreWeave (CRWV) shares plummeted 13% after CEO Mike Intrator cited data center delays impacting its full-year projections. While Intrator portrayed the issue as isolated, CNBC’s Jim Cramer suggested broader problems, potentially tied to Core Scientific (CORZ), whose shares also fell 7%. CoreWeave revised its 2025 revenue forecast downwards despite a strong third-quarter revenue growth of 134%. The market reacted to the ambiguity surrounding the delays’ extent and their potential impact on CoreWeave’s ability to fulfill major AI infrastructure contracts with companies like Meta and OpenAI.

CoreWeave, an AI-focused cloud provider, reported strong Q3 earnings, exceeding revenue expectations with $1.36 billion, a 134% year-over-year increase. While reporting a net loss, it was significantly improved compared to the previous year. The company boasts a $55.6 billion contracted backlog and secured major partnerships with OpenAI and Meta. Since its March IPO, the stock has risen 164%. However, a proposed acquisition of Core Scientific was rejected. Investors are watching for updates on capacity expansion and profitability strategies.

This week’s portfolio adjustments involve a partial sale of Cisco (CSCO) due to security revenue concerns, despite long-term AI optimism. Proceeds are strategically reinvested into Corning (GLW) and Meta Platforms (META). Corning is expected to benefit from growing demand for fiber optic solutions driven by AI data center infrastructure. Meta is seen as undervalued after a recent pullback, presenting an attractive entry point based on its AI potential and monetization capabilities.. These moves aim to balance risk and capitalize on long-term growth trends in AI and data infrastructure.

OpenAI CFO Sarah Friar clarified that the company is not seeking a government “backstop” for its infrastructure plans, despite earlier suggestions. Instead, she emphasized a collaborative approach between the private sector and government to build U.S. technological capacity. This comes as OpenAI undertakes $1.4 trillion in infrastructure agreements to meet AI demand. Friar projects $13B+ revenue this year, but spending commitments have raised concerns about financial sustainability, which CEO Sam Altman dismissed. Friar highlighted ongoing collaboration with the U.S. government, underscoring AI’s role as a national strategic asset.

OpenAI projects over $20 billion in annualized revenue this year, aiming for hundreds of billions by 2030. CEO Sam Altman emphasizes massive infrastructure expansion to meet AI model demand, with reported deals exceeding $1.4 trillion. CFO Sarah Friar’s suggestion of a potential federal “backstop” for semiconductor investments sparked controversy and was later clarified, with OpenAI asserting they do not seek government guarantees for data centers, relying instead on private sector investment. Analysts highlight the risks and competition in OpenAI’s aggressive expansion strategy.

Google has launched its seventh-generation Tensor Processing Unit (TPU), Ironwood, now generally available to cloud customers. This custom-designed AI accelerator aims to rival Nvidia GPUs by offering specialized, high-performance computing power for AI workloads like training LLMs and real-time inference. Ironwood boasts interconnectivity of up to 9,216 TPUs in a single pod. AI startup Anthropic has pledged to utilize up to 1 million Ironwood TPUs. The move underscores Google’s commitment to AI infrastructure amid growing cloud revenue and increased capital expenditure.

Super Micro Computer (SMCI) shares plunged 10% in after-hours trading as fiscal first-quarter results missed analyst expectations. EPS was 35 cents (adj.) versus 40 cents expected, and revenue reached $5.02 billion, below the $6 billion forecast. Revenue declined 15% year-over-year. Net income also more than halved. The company cited “design win upgrades” for the shortfall, shifting revenue to Q2, where they now forecast $10-$11 billion in sales. Despite benefiting from AI growth, SMCI’s growth seems to have slowed amid increasing competition.

Penguin Solutions will showcase its HPC and AI infrastructure advancements at Supercomputing 25 (SC25) in St. Louis, November 16-21, 2025. Attendees will gain insights into manageability, scalability, and performance for advanced AI solutions. Highlights include demonstrations of Penguin’s technologies and its partnership with SK Telecom on Haein, a large-scale AI factory powered by NVIDIA Blackwell GPUs, enabling national AI strategies. Penguin Solutions aims to optimize AI workflows and accelerate time-to-insight.

Cloud computing firm Lambda has secured a multi-billion dollar deal with Microsoft to provide AI infrastructure, driven by surging demand for AI services. The agreement involves deploying tens of thousands of Nvidia GPUs. Lambda CEO Stephen Balaban cited widespread adoption of AI services like ChatGPT and Claude as key drivers. This partnership strengthens the existing relationship between Lambda and Microsoft, bolstering Microsoft’s AI cloud offerings. Lambda will utilize NVIDIA GB300 NVL72 systems. Lambda also plans to launch a new AI factory in Kansas City by 2026, reflecting long-term growth in AI infrastructure.

OpenAI is diversifying its AI compute supply chain with a multi-year, $38 billion agreement with AWS, moving away from its previous exclusive cloud partnership with Microsoft. This strategic shift to a multi-cloud architecture signifies the rising importance and scarcity of high-performance GPUs. AWS will provide OpenAI access to NVIDIA GPUs and CPUs to support training and inference. This move highlights the end of single-cloud strategies and the escalation of AI budgeting to corporate capital planning, emphasizing risk diversification and long-term financial commitments for AI infrastructure.