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The most innovative companies in computing this year reflect wide-ranging efforts to build the infrastructure that next-generation AI applications require, and to enable their deployment in virtually any imaginable location or scenario. Nvidia\u2019s<\/a> GB300 NVL72 platform, an \u201cAI supercomputer\u201d\u2014incorporating GPUs, CPUs, power, cooling and networking components\u2014delivers 50x the reasoning power of prior systems. It is already being deployed by hyperscalers and cloud platforms such as CoreWeave and Microsoft Azure.<\/p>\n<\/div>\n This year saw a proliferation of data centers to power AI. \u201cNeocloud\u201d providers such as Nebius<\/a> are commoditizing and democratizing access to GPU clusters with strategic hubs across the U.S. and Europe, serving customers that include Microsoft and Meta. Crusoe<\/a> began operating the first two buildings of a planned 1.2 gigawatt site for OpenAI\u2019s and Oracle\u2019s $500 billion Project Stargate,\u00a0The Abilene, Texas facility will be one of the largest in the world, powered by wind with natural-gas turbines for backup. Meanwhile, Armada<\/a> is building modular, redeployable data centers for remote and rugged industrial applications, serving customers in defense, energy, mining, telecommunications, and public infrastructure.<\/p>\n Tackling bottlenecks that conventional hardware can no longer solve, Ayar Labs<\/a> is building optical components that replace copper wiring for faster, more efficient computing, while Sandisk\u2019s<\/a> High Bandwidth Flash memory, built specifically for AI inference workloads, delivers 8x to 16x the capacity of traditional high-bandwidth memory at a similar cost. In semiconductor manufacturing, xLight<\/a> is leveraging particle-accelerator research in its \u201cfree-electron\u201d laser, which could push past current limitations in extreme ultraviolet lithography.\u00a0\u00a0<\/p>\n This year\u2019s list also recognizes a maturing quantum computing sector, with Google, Amazon (via AWS<\/a>), and Quantinuum<\/a> demonstrating novel architectures, achieving breakthroughs in error correction, and blowing past classical computing benchmarks. And PsiQuantum<\/a>, having made it to the final stage of DARPA\u2019s Quantum Benchmarking program,\u00a0scored record-breaking investments.<\/p>\n<\/div>\n For consistently setting the standard for chips to power AI <\/em><\/p>\n Chip designer NVIDIA reached a $4.5 trillion market cap in 2025 by creating the infrastructure powering the AI boom. As companies shift from training AI models to deploying them at scale, it has kept pace by designing high-performing systems that power large-scale reasoning and keep data centers smoothly humming.<\/p>\n In 2025, the company released its GB300 NVL72 platform, merging 72 Blackwell Ultra GPUs and 36 NVIDIA Grace CPUs in a package that functions as a plug-and-play rack-scale AI supercomputer. It integrates innovations in liquid cooling, power management, networking, and software and delivers 50x the reasoning power of previous-generation systems. Tasks that once took weeks can be completed in just hours. And each rack of the GB300 NVL72 also delivers significantly more performance per watt than past systems, while using power management algorithms intended to stabilize the grid.\u00a0<\/p>\n<\/div>\n1. Nvidia<\/h2>\n