Liquid Cooling
A thermal management technology that uses liquid coolant instead of air to remove heat from AI chips and servers, essential for managing the extreme heat density of modern GPU clusters.
A single NVIDIA H100 GPU generates up to 700W of heat, and a rack of 8 GPUs can produce 10kW+, exceeding the capacity of traditional air cooling. Direct-to-chip liquid cooling reduces cooling energy consumption by 30-40% compared to air cooling. NVIDIA's B200 GPU essentially requires liquid cooling due to its 1000W+ thermal design power. Over 40% of new AI-optimized data centers are being built with liquid cooling infrastructure. The liquid cooling market for data centers is projected to exceed $10 billion by 2027, driven almost entirely by AI compute density.
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Related Terms
AI Compute
The computational resources — primarily GPU and TPU processing power — required to train and run AI models, typically measured in FLOP (floating-point operations) or GPU-hours.
Capex (Capital Expenditure)
Long-term investment spending by companies on physical assets like data centers, GPU clusters, and networking infrastructure — the backbone of AI deployment at scale.
ChatGPT
OpenAI's conversational AI assistant, launched in November 2022, which catalyzed the current generative AI boom by demonstrating the capabilities of large language models to a mainstream audience.
Data Center
A facility housing computer systems and infrastructure used to process, store, and distribute data — increasingly built specifically for AI training and inference workloads.
Fine-Tuning
The process of further training a pre-trained AI model on a specific, smaller dataset to specialize it for a particular task or domain, requiring far less compute than training from scratch.
Foundation Model
A large AI model trained on broad data that can be adapted to a wide range of downstream tasks — examples include GPT-4, Claude, Gemini, and Llama.
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