China’s “Manhattan Project” aims to upend the AI industry by 2031. Imagine a high-end GPU for just $1,000—a price point that could collapse Nvidia’s margins, trap Neoclouds in debt, and turn elite compute into a common utility.
China’s 2031 roadmap, fueled by domestic EUV and “CUDA Killer” stacks, threatens Western AI dominance. Meanwhile, Google’s $4.75B leap into energy infrastructure signals a massive shift: the battle for AI will be won at the wellhead.
The AI infrastructure market is fracturing under recession pressures, runaway memory shortages, and a surge of new competitors. Our Q4 2025 snapshot breaks down the chaos, highlights major shifts, and tracks how the industry is reshaping itself in real time.
Building GPU cloud infrastructure is capital-intensive. Hyperscalers and AI cloud providers invest billions in NVIDIA GPUs, often using debt or equity. How they account for hardware’s useful life directly impacts margins, cash flow, and investor perception.
Talk of an AI bubble is intensifying, fueled by recent high-profile agreements among Oracle, OpenAI, Nvidia, and CoreWeave. These unconventional deals recall the complex IRU swap structures once executed by Qwest and Global Crossing two decades ago.
Oracle stunned Wall Street on Tuesday when it announced that OCI (cloud) revenue will jump from $20 billion to $144 billion in four years. That’s only the tip of the iceberg. Public AI infrastructure companies such as CoreWeave, Nebius, and
Positron is a pioneering company specializing in purpose-built hardware designed to accelerate multimodal AI, particularly focusing on transformer model inference. The company recently appointed Mitesh Agrawal as CEO, bringing in a leader with extensive experience in AI infrastructure. Previously the
The graphics card in the computer (“AI workstation”) is the key to maximizing the computing performance of an AI model. The AI workstation is available as DIY (build your own), in the cloud, or both. For organizations that have embraced
