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Hotter Than a Hot Tub: The 45°C Breakthrough to Cool AI’s Biggest Machines

07:00 · June 22, 2026 · NVIDIA

Hotter Than a Hot Tub: The 45°C Breakthrough to Cool AI’s Biggest Machines

Hot tubs sit at about 38 to 40 degrees Celsius, warm enough that most people can only soak for about 15 minutes. NVIDIA’s newest AI servers can run their cooling liquid even hotter — up to 45 degrees Celsius, or 113 degrees Fahrenheit. That higher temperature limit is precisely what makes them more energy efficient. […]

Summary

NVIDIA’s Rubin-generation AI servers mark the first full transition to 100 percent liquid cooling, with every processor, networking component and supporting element served by a closed-loop system that operates without fans or cold-aisle infrastructure. Coolant enters cold plates at up to 45 °C—roughly five degrees warmer than a typical hot-tub temperature—exits at about 55 °C and is routed through a mixture of 75 percent water and 25 percent propylene glycol. Because the liquid captures heat directly at the chip, the surrounding data-center air can remain at ambient outdoor temperatures for most of the year.

The approach is formalized in the NVIDIA DSX AI factory reference design, which specifies dry-cooler rejection loops that eliminate evaporative cooling towers. In suitable climates the facility can run chiller-free except for perhaps one percent of annual hours, cutting cooling-related electricity use that historically reached 40 percent of total data-center demand. Industry estimates indicate each additional degree of allowable coolant temperature reduces cooling energy by roughly four percent; at hyperscale, a 50-megawatt installation can therefore save more than four million dollars annually in combined energy and water costs while reducing water consumption from approximately 2.6 million gallons per megawatt-year to near zero.

Beyond efficiency, the sealed liquid architecture removes the perforated bezels and high-speed fans of earlier hybrid designs, lowering rack noise below the 85-decibel threshold that once required ear protection and allowing previously six-rack-unit assemblies to fit in two rack units. The same higher-temperature loop also opens the possibility of waste-heat recovery for nearby buildings. Every cloud provider and operator adopting the Rubin platform must therefore re-engineer its cooling stack, a shift already supported by long-standing partners such as Motivair, now part of Schneider Electric, whose cold-plate and coolant-distribution units have tracked NVIDIA’s power-density roadmap for nearly a decade.

Why it matters

This article is highly relevant as it addresses the critical environmental impact of AI data centers, a major concern in the Netherlands given its dense data center footprint. The breakthrough in liquid cooling offers significant energy and water savings, which is vital for Dutch enterprises and policymakers focused on sustainable AI infrastructure.

More in this beat
cloud-computingdeployment-readinessDSX AI factoryinference-performanceliquid-coolingnvidiarubin
Run AI workloads on any cloud, store on Hugging Face: zero-egress storage with SkyPilot

02:00 · July 7, 2026

Run AI workloads on any cloud, store on Hugging Face: zero-egress storage with SkyPilot

This article provides ML Engineers with a practical, hands-on solution to a major MLOps pain point: high egress costs in multi-cloud GPU environments. It offers actionable code snippets and benchmarks that AI teams can immediately implement to optimize their cloud compute budgets and avoid vendor lock-in.

Relevance 85 · Audience 95

How NVIDIA’s Inference Software Stack Powers the Lowest Token Cost

17:00 · June 30, 2026

How NVIDIA’s Inference Software Stack Powers the Lowest Token Cost

This article is relevant because it addresses a critical bottleneck in AI adoption: inference costs. For Dutch enterprises and SMEs scaling AI from pilots to production, understanding how software optimizations lower the cost per token is essential for sustainable AI deployment.

Relevance 75 · Audience 65

A Year in LLM Serving: Workload Evolution, Caching and Load-Balancing

06:00 · August 17, 2026

A Year in LLM Serving: Workload Evolution, Caching and Load-Balancing

This research provides a rare, large-scale dataset and analysis of real-world LLM serving workloads, which is crucial for Dutch AI infrastructure researchers and cloud providers aiming to optimize model deployment, caching, and load-balancing. The release of the full trace enables reproducible benchmarking for local AI systems engineering.

Relevance 85 · Audience 95

GPU Management: Why Idle GPUs Are the New Grounded Aircraft

17:09 · July 30, 2026

GPU Management: Why Idle GPUs Are the New Grounded Aircraft

It addresses critical MLOps and production challenges faced by ML Engineers, specifically GPU utilization, workload scheduling, and compute cost optimization. For Dutch enterprises and SMEs scaling AI, mastering these orchestration strategies is essential to remain cost-effective without relying on massive hardware budgets.

Relevance 75 · Audience 85

Bringing Nunchaku 4-bit Diffusion Inference to Diffusers

02:00 · July 23, 2026

Bringing Nunchaku 4-bit Diffusion Inference to Diffusers

Directly addresses production challenges of VRAM and latency for diffusion models with quantitative benchmarks and actionable Diffusers workflows that Dutch ML teams can apply immediately.

Relevance 85 · Audience 90

NVIDIA Introduces New Jetson Thor Computers to Advance Mainstream Robotics and Edge AI

01:00 · July 16, 2026

NVIDIA Introduces New Jetson Thor Computers to Advance Mainstream Robotics and Edge AI

This article highlights crucial advancements in edge AI and robotics hardware, which are key growth areas for the Dutch AI market, particularly in logistics, agriculture, and smart retail. It provides a general AI audience with insights into how foundation models are transitioning from labs to real-world physical applications.

Relevance 85 · Audience 75

NVIDIA Nemotron Achieves Benchmark-Leading Performance With LangChain Deep Agents Harness

17:00 · July 8, 2026

NVIDIA Nemotron Achieves Benchmark-Leading Performance With LangChain Deep Agents Harness

This development is highly relevant as it offers a cost-effective, open-source alternative to closed AI models, which is crucial for driving AI adoption among Dutch SMEs. Furthermore, the ability to run these agents on proprietary infrastructure aligns perfectly with European data sovereignty and strict AI governance requirements.

Relevance 85 · Audience 75

AI Innovators Adopt NVIDIA Vera — Why Max Single-Threaded CPU at Scale Matters

17:00 · July 7, 2026

AI Innovators Adopt NVIDIA Vera — Why Max Single-Threaded CPU at Scale Matters

This article highlights a critical shift in AI infrastructure hardware necessary for the emerging agentic AI era. For the Dutch AI market, understanding these hardware advancements is vital for optimizing data center investments and deploying efficient, scalable AI agents.

Relevance 85 · Audience 75

Hugging Face and Cerebras bring Gemma 4 to real-time voice AI

02:00 · July 1, 2026

Hugging Face and Cerebras bring Gemma 4 to real-time voice AI

This article is highly relevant for ML Engineers as it provides a practical, open-source architecture for solving critical latency bottlenecks in real-time voice AI. Dutch AI teams can directly implement this modular stack using the provided repositories to build responsive conversational agents and embodied AI solutions.

Relevance 80 · Audience 90

Accelerating Transformers Fine-Tuning with NVIDIA NeMo AutoModel

18:00 · June 24, 2026

Accelerating Transformers Fine-Tuning with NVIDIA NeMo AutoModel

Directly addresses hands-on tooling for ML engineers with specific algorithmic optimizations, benchmarks, and implementation patterns for large-scale MoE fine-tuning that Dutch AI practitioners can apply immediately.

Relevance 88 · Audience 95