Traditionally, data centers have relied on air cooling—where mechanical chillers circulate chilled air to absorb heat from servers, helping them maintain optimal conditions. But as AI models increase in size, and the use of AI reasoning models rises, maintaining those optimal conditions is not only getting harder and more expensive—but more energy-intensive. While data centers once operated at 20 kW per rack, today's hyperscale facilities can support over 135 kW per rack, making it an order of magnitude harder to dissipate the heat generated by high-density racks. To keep AI servers running at peak performance, a new approach is needed for efficiency and scalability.

One key solution is liquid cooling—by reducing dependence on chillers and enabling more efficient heat rejection, liquid cooling is driving the next generation of high-performance, energy-efficient AI infrastructure. The NVIDIA GB200 NVL72 and the NVIDIA GB300 NVL72 are rack-scale, liquid-cooled systems designed to handle the demanding tasks of trillion-parameter large language model inference. Their architecture is also specifically optimized for test-time scaling accuracy and performance, making it an ideal choice for running AI reasoning models while efficiently managing energy costs and heat.

Supermicro, Inc., a Total IT Solution Provider for AI, Cloud, Storage, and 5G/Edge, is announcing new systems and rack solutions powered by the NVIDIA's Blackwell Ultra platform, featuring the NVIDIA HGX B300 NVL16 and NVIDIA GB300 NVL72 platforms. Supermicro and NVIDIA's new AI solutions strengthen leadership in AI by delivering breakthrough performance for the most compute-intensive AI workloads, including AI reasoning, agentic AI, and video inference applications.

"At Supermicro, we are excited to continue our long-standing partnership with NVIDIA to bring the latest AI technology to market with the NVIDIA Blackwell Ultra Platforms," said Charles Liang, president and CEO, Supermicro. "Our Data Center Building Block Solutions approach has streamlined the development of new air and liquid-cooled systems, optimized to the thermals and internal topology of the NVIDIA HGX B300 NVL16 and GB300 NVL72. Our advanced liquid-cooling solution delivers exceptional thermal efficiency, operating with 40℃ warm water in our 8-node rack configuration, or 35℃ warm water in double-density 16-node rack configuration, leveraging our latest CDUs. This innovative solution reduces power consumption by up to 40% while conserving water resources, providing both environmental and operational cost benefits for enterprise data centers."

Giga Computing, a subsidiary of GIGABYTE and an industry leader in generative AI servers and advanced cooling technologies, today announced participation at NVIDIA GTC 2025 to bring to the market the best in GPU-based solutions for generative AI, media acceleration, and large language models (LLM). To this end, GIGABYTE booth #1409 at NVIDIA GTC showcases a rack-scale turnkey AI solution, GIGAPOD, that offers both air and liquid-cooling designs for the NVIDIA HGX B300 NVL16 system. Also, on display at the booth is a compute node from the newly announced NVIDIA GB300 NVL72 rack-scale solution. And for modularized compute architecture are two servers supporting the newly announced NVIDIA RTX PRO 6000 Blackwell Server Edition.

Complete AI solution - GIGAPOD
With the depth of expertise in hardware and system design, Giga Computing has combined infrastructure hardware, platform software, and architecting service to deliver scalable units composed of GIGABYTE GPU servers with NVIDIA GPU baseboards, while running GIGABYTE POD Manager, a powerful software suite designed to enhance operational efficiency, streamline management, and optimize resource utilization. GIGAPOD's scalable unit is designed for either nine air-cooled racks or five liquid-cooled racks. Giga Computing offers two approaches for the same goal, one powerful GPU cluster using NVIDIA HGX Hopper and Blackwell GPU platforms at scale to meet demand for all AI data centers.

ASUS today joined GTC 2025 as a Diamond sponsor to showcase the latest ASUS AI POD with the NVIDIA GB300 NVL72 platform. The company is also proud to announce that it has already garnered substantial order placements, marking a significant milestone in the technology industry. At the forefront of AI innovation, ASUS also presents the latest AI servers in the Blackwell and HGX family line-up. These include ASUS XA NB3I-E12 powered by NVIDIA B300 NVL16, ASUS ESC NB8-E11 with NVIDIA DGX B200 8-GPU, ASUS ESC N8-E11V with NVIDIA HGX H200, and ASUS ESC8000A-E13P/ESC8000-E12P supporting NVIDIA RTX PRO 6000 Blackwell Server Edition with MGX architecture. With a strong focus on fostering AI adoption across industries, ASUS is positioned to provide comprehensive infrastructure solutions in combination with the NVIDIA AI Enterprise and NVIDIA Omniverse platforms, empowering clients to accelerate their time to market.

By integrating the immense power of the NVIDIA GB300 NVL72 server platform, ASUS AI POD offers exceptional processing capabilities—empowering enterprises to tackle massive AI challenges with ease. Built with NVIDIA Blackwell Ultra, GB300 NVL72 leads the new era of AI with optimized compute, increased memory, and high-performance networking, delivering breakthrough performance.

NVIDIA today unveiled NVIDIA DGX personal AI supercomputers powered by the NVIDIA Grace Blackwell platform. DGX Spark—formerly Project DIGITS—and DGX Station, a new high-performance NVIDIA Grace Blackwell desktop supercomputer powered by the NVIDIA Blackwell Ultra platform, enable AI developers, researchers, data scientists and students to prototype, fine-tune and inference large models on desktops. Users can run these models locally or deploy them on NVIDIA DGX Cloud or any other accelerated cloud or data center infrastructure.

DGX Spark and DGX Station bring the power of the Grace Blackwell architecture, previously only available in the data center, to the desktop. Global system builders to develop DGX Spark and DGX Station include ASUS, Dell, HP Inc. and Lenovo.

NVIDIA today announced the next evolution of the NVIDIA Blackwell AI factory platform, NVIDIA Blackwell Ultra—paving the way for the age of AI reasoning. NVIDIA Blackwell Ultra boosts training and test-time scaling inference—the art of applying more compute during inference to improve accuracy—to enable organizations everywhere to accelerate applications such as AI reasoning, agentic AI and physical AI.

Built on the groundbreaking Blackwell architecture introduced a year ago, Blackwell Ultra includes the NVIDIA GB300 NVL72 rack-scale solution and the NVIDIA HGX B300 NVL16 system. The GB300 NVL72 delivers 1.5x more AI performance than the NVIDIA GB200 NVL72, as well as increases Blackwell's revenue opportunity by 50x for AI factories, compared with those built with NVIDIA Hopper.

TrendForce reveals that the combined revenue of the world's top 10 IC design houses reached approximately US$249.8 billion in 2024, marking a 49% YoY increase. The booming AI industry has fueled growth across the semiconductor sector, with NVIDIA leading the charge, posting an astonishing 125% revenue growth, widening its lead over competitors, and solidifying its dominance in the IC industry.

Looking ahead to 2025, advancements in semiconductor manufacturing will further enhance AI computing power, with LLMs continuing to emerge. Open-source models like DeepSeek could lower AI adoption costs, accelerating AI penetration from servers to personal devices. This shift positions edge AI devices as the next major growth driver for the semiconductor industry.

NVIDIA "Blackwell" series is barely out with B100, B200, and GB200 chips shipping to OEMs and hyperscalers, but the company is already setting in its upgraded "Blackwell Ultra" plans with its upcoming GB300 AI server. According to UDN, the next generation NVIDIA system will be powered by the B300 GPU chip, operating at 1400 W and delivering a remarkable 1.5x improvement in FP4 performance per card compared to its B200 predecessor. One of the most notable upgrades is the memory configuration, with each GPU now sporting 288 GB of HBM3e memory, a substantial increase from the previous 192 GB of GB200. The new design implements a 12-layer stack architecture, advancing from the GB200's 8-layer configuration. The system's cooling infrastructure has been completely reimagined, incorporating advanced water cooling plates and enhanced quick disconnects in the liquid cooling system.

Networking capabilities have also seen a substantial upgrade, with the implementation of ConnectX 8 network cards replacing the previous ConnectX 7 generation, while optical modules have been upgraded from 800G to 1.6T, ensuring faster data transmission. Regarding power management and reliability, the GB300 NVL72 cabinet will standardize capacitor tray implementation, with an optional Battery Backup Unit (BBU) system. Each BBU module costs approximately $300 to manufacture, with a complete GB300 system's BBU configuration totaling around $1,500. The system's supercapacitor requirements are equally substantial, with each NVL72 rack requiring over 300 units, priced between $20-25 per unit during production due to its high-power nature. The GB300, carrying Grace CPU and Blackwell Ultra GPU, also introduces the implementation of LPCAMM on its computing boards, indicating that the LPCAMM memory standard is about to take over servers, not just laptops and desktops. We have to wait for the official launch before seeing LPCAMM memory configurations.