The rapid adoption of artificial intelligence (AI) has led to increased demand for more powerful chips in data centers for training complex large language models (LLMs) and deploying those models through AI inference. This development has created two significant challenges for data centers: reducing electricity consumption and managing higher heat generation. According to market research firm IDC, energy consumption in AI data centers is expected to grow at a compound annual rate of 45% until 2027, potentially doubling overall electricity use between 2023 and 2028. Goldman Sachs also forecasts a 160% increase in data center power demand by 2030.
Two companies, Nvidia and Super Micro Computer, are positioned to address these challenges. Nvidia’s graphics processing units (GPUs) are widely used in AI training and inference, commanding over 85% of the AI chip market. The company’s next-generation Blackwell AI processors promise significant reductions in energy consumption and performance improvements, allowing large AI models like OpenAI’s GPT-4 to be trained with substantially less power. Analysts at Mizuho predict that Nvidia’s revenue could exceed $200 billion by 2027, tripling its fiscal 2024 revenue, suggesting strong future demand for its chips.
Super Micro Computer, despite recent market challenges, is focusing on addressing heat generation issues in AI data centers with its liquid-cooled server solutions. The company has already shipped a significant number of liquid-cooled server racks and anticipates deploying more GPUs using these solutions. Supermicro claims its technology can achieve up to 40% energy savings and 80% space savings, which drives strong demand for its products. The overall market for liquid-cooled data centers is projected to grow significantly, presenting Supermicro with increased opportunities. Despite concerns, Supermicro’s earnings are expected to grow at an annual rate of 62% over the next five years, making it an appealing option for investors aiming to capitalize on AI-related opportunities.
