
Stargate Abilene has become the symbol of America’s AI buildout. It is a gigawatt-scale campus on the Texas plains built for OpenAI. China has campuses on a similar scale, though few people outside the country have had a look inside. In September, we visited one, and we found the speed, scale, ultra low cost, and deep vertical integration astonishing.During the trip, we toured Inner Mongolia, China’s fastest-growing AI datacenter region. It's the “West Texas” of China, bu

We wrote at length about how SpaceX’s plans for 10GW in 2027 was feasible, paving the way for +300b+ ARR. We received a lot of pushback from folks calling it impossible. Now, just two months later, we’re already seeing 3.6GW under construction across multiple sites, both existing and new. SpaceX has even revised its estimate up to ~13GW in 2027. This would be the largest amount of datacenter capacity ever built by any one company in that timeframe, roughly equivalent to all of Google

Data center developers are poised to face a more restrictive building environment after voters across the country voted in candidates who favor moratoriums and ballot measures that put more obstacles on their expansion, delivering a stinging blow to a central pillar of the AI industry. Of voters polled by NBC News on Election Day, 76 percent said they opposed data centers in their communities. Dozens of local communities voted directly to restrict development through ballot mea
Also reported by Wired AI and TechCrunch

The deal highlights the challenges of developing massive AI data centers.

Huawei’s AI data center in Horinger, Inner Mongolia, uses Ascend chips and has an estimated AI computing capacity that is just 7% that of the world’s largest AI data center, SpaceX’s Colossus 2 in Tennessee.

Members of the action group Geef Tegengas put a banner on a crane during a protest. | Image: Getty Images Protesters have broken into a construction site of a new Microsoft data center in Amsterdam this morning. Members of the Geef Tegengas group helped organize the protest against the construction of three 85-meter data center towers in the outskirts of Amsterdam. Reuters reports that around 100 people made it into the construction site, with some scaling a crane to place a "fu

In November 2025, we published a newsletter saying that Google is selling TPUs to external customers. Since then, we have been proven right over and over again with Oracle, OpenAI, Anthropic, and Meta all becoming customers of TPUs just as our Accelerator Model reported.Hardware demand is only half the story, as NVIDIA’s moat has historically been its software and large developer ecosystem. This is where TPU is also making headway, partnering with upstream maintainers across the entire ec

Larger models, longer contexts and agentic applications are increasing GPU memory pressure while supply tightens and prices rise — a trend expected to continue through the near term. NVIDIA works closely with memory partners to rapidly adopt the latest memory technologies. NVIDIA was first to adopt HBM3e and HBM4 technologies into an accelerated computing stack. But the approach isn’t to simply pack more memory onto the GPU. It’s full-stack codesign. NVIDIA intentionally designs GPUs, CPUs, net

After four of the biggest competitors in the AI race held quarterly earnings calls late last month, two things are clear: Big Tech is not done spending record amounts on the AI data center buildout, and the AI data center buildout is not any closer to yielding its promised returns. A third thing is also starting to become clear - Big Tech will not be slowing down, at least not on its own. Amazon, Microsoft, Alphabet, and Meta told investors they're planning to spend at least $7

AI data center demand is reviving nuclear energy, but whether SMRs, plant restarts, and fusion can deliver enough power quickly remains uncertain.

Broadcom’s shipments of TPU by unit volume increased by about 65% quarter over quarter to roughly 800,000 chips, while compute output doubled, driven by a shift to more powerful chips.

Crusoe's 3.5 MW Spark Liquid unit highlights how factory-built, modular data centers are becoming a faster path to AI capacity at scale.

The years-long wait for access to the grid and new turbines is causing data center builders to turn to an unusual, less efficient and less environmentally friendly solution: once-discarded jet engines.

Russian tech companies are scrambling to harden and hide their data centers underground after Ukrainian drone strikes damaged facilities housing AI supercomputers and disrupted cloud services for millions of Russian users. Meanwhile, the Kremlin is requiring data center owners to reserve computing capacity for emergency state needs and has even authorized possible use of foreign data centers. These consequences of Russia's war against Ukraine come as the Russian military has bombarded Ukrainian

Lumai is testing optical AI servers in a UK lab to see whether shifting inference prefill off GPUs can ease data center power constraints.

Zyphra has released ZYFA (Zyphra FlashAttention on AMD), a set of FP8 and BF16 prefill attention kernels for AMD Instinct MI355X GPUs. ZYFA is Zyphra’s FP8 attention engine for long-context prefill, and the code is open source under Apache 2.0. On real model activations, its FP8 kernels run 1.16-1.76x faster than AITER, AMD’s default kernel library. At head dimension 128, ZYFA’s FP8 error is 62-78% lower than AITER’s. TL;DR Framework: It is a kernel library. Causa

A year ago, NVIDIA open sourced its Aerial wireless software, joining Sionna and a broader suite of open source tools for accelerating next-generation 6G network development. Together, they give researchers a foundation for testing ideas, comparing results and building on each other’s work — connecting simulation and AI training with experiments on real over-the-air wireless systems. Today, researchers and developers are using these tools to build 6G-ready networks that do more than just transmi

AI agents do more than generate answers. They search for information, query databases, write and test code and take action. Each of those steps relies on a CPU, with agents moving between GPU reasoning and CPU execution throughout a task. As businesses put more agents to work, AI factories need CPUs that can execute those steps quickly and support many agents at once, all within the limits of available power. What this means: AI infrastructure providers need to support more agents without maki
Operational sovereignty gives universities authority over how shared computing resources are allocated, managed and secured. The University of Utah’s Redtail AI factory supercomputer brings advanced computing capabilities to a statewide community. Supporting researchers, students, administrators and external partners through that infrastructure requires more than computing capacity, according to Manish Parashar (pictured), chief AI officer of […] The post University of Utah retains operati

After Democrats won big in Texas and other AI infrastructure hot spots on Tuesday, data center enthusiasts looked for comfort in low Earth orbit.

With smartphone sales tanking by around 20 percent compared to 2025, Qualcomm is looking to data centers to help boost its bottom line. During its Q4 2026 earnings call, the company laid out its plans to make a splash in the AI data center business, through partnerships with companies like Amazon and Meta announced earlier this year. The company expects that portion of its business to grow quickly, forecasting around $650 million in data center revenue during the first quarter

NVIDIA’s latest technical blog shows how to speed up mixture-of-experts (MoE) inference on one DGX Spark. The test model is Ant Group inclusionAI’s Ling-3.0-flash, a 124B-parameter MoE with 5.1B active parameters. NVIDIA stacked three optimizations: a new MoE kernel backend, an FP8 output layer and built-in speculative decoding. On all 1,319 GSM8K questions, decode throughput rose 42.5% with no statistically detectable accuracy change. So why is it relevant for Devs? DGX Spark is a desktop s

Trump’s onsite power push highlights a hard reality: most AI data centers will likely need hybrid energy strategies rather than fully off-grid designs.
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