The rapid development and deployment of massive artificial intelligence (AI) in the cloud - including OpenAI's ChatGPT, Microsoft's Bing with AI, plus Google's Bard and Deep Mind Gemini - is drawing new and more powerful, purpose-designed AI processors into data center. The rapid development and deployment of massive artificial intelligence (AI) in the cloud - including OpenAI's ChatGPT, Microsoft's Bing with AI, plus Google's Bard and Deep Mind Gemini - is drawing new and more powerful, purpose-designed AI processors into data center. Data centers evolve to meet AI's massive power needs Technical Article Data centers evolve to meet AI's massive power needs Brent McDonald, systems and applications engineer, Texas Instruments With large language models revolutionizing how we access data, artificial intelligence (AI) advancements. AI is rapidly transforming data center design, driving a new level of densification across the industry. As GPU-intensive workloads scale, operators are packing significantly more compute power into the same physical footprint, which results in higher kW per rack, greater heat output, and increased. Demand for AI accelerators is rapidly increasing rack power density, with projections approaching 1MW per deployment by 2027. This poses a major challenge for datacenter power delivery designers. As power densities increase, a datacenter designed for a different target density may strand power. Surging AI power needs dictate a new datacenter power architecture: shifting to 800 V DC distribution, using "SideCar" racks, and employing GaN/SiC for high-density, vertical power delivery. This article is published by EEPower as part of an exclusive digital content partnership with Bodo's Power. Consequently, AI data centers, referring to computing facilities specifically designed for large-scale artificial intelligence workloads, have become one of the fastest-growing electricity consumers globally. The rise of artificial intelligence (AI) has significantly increased computing.