Data centre operators and researchers are shifting from copper wiring toward photonics to cut the energy used by power distribution, cooling, and heat from electronic networking. A typical 100MW data centre uses about 400 tonnes of copper, including up to 70 tonnes in servers and up to 20 tonnes in network wiring. This changes data-centre infrastructure by replacing some copper interconnects with light-based optical links while requiring new manufacturing, installation, and thermal-reliability practices before wider deployment.
Hundreds of workers are building new data centres in rural Inner Mongolia to supply the computing power behind China’s AI platforms. The article says China is building “hundreds” of data centres across provinces including Ulanqab and aims to embed AI across 90% of industries and society by 2030. As a result, infrastructure and power generation plans expand while some rural communities report village relocations and limited local benefits, even as others see job opportunities and faster AI innovation.
BBC reporter Laura Bicker visited Inner Mongolia to describe how Chinese data centres are being built to support the country’s artificial intelligence ambitions. Dozens of data centres are under construction there. The reporting highlights differing attitudes toward the data centre industry in China versus the US ahead of Xi Jinping and Donald Trump meeting in Washington later this week.
Qualcomm announced the Snapdragon 8 Elite Gen 6 and Snapdragon 8 Elite Extreme Gen 6 smartphone chips with an emphasis on on-device AI features. The Extreme model can run a 30-billion-parameter mixture-of-experts model locally while activating only part of the parameters for each task. As a result, phones can support locally run personal voice agents and sensing hubs that enable speaker differentiation, task automation suggestions, and higher-end camera/video capabilities.
Motorola announced the Signature 27 as its first phone to use Qualcomm’s Snapdragon 8 Elite Extreme Gen 6 chipset. The Extreme Gen 6 is Qualcomm’s top-end model. The launch positions Motorola’s next flagship as its most advanced in years, though exact specs, price, and release date are still not provided.
Qualcomm announced the Snapdragon 8 Elite Gen 6, and also released the Snapdragon 8 Elite Extreme Gen 6 alongside it. The chips are built on a 2nm process. The Extreme model mainly changes AI processing, video capture, and gaming performance versus the standard Gen 6 while keeping most other core specs the same.
CoolIT says that above 250 kW per rack, liquid-air hybrid cooling becomes impractical and it shifts to near-total heat capture to enable fanless liquid-cooled AI servers. It claims air can fall below 1% of the load, with a 70/30 liquid-air split leaving 75 kW to be handled by air. This changes server design toward integrating all components into a single liquid loop built from modular coldplate blocks rather than relying on air cooling for non-CPU parts.
NVIDIA released Isaac ROS 5.0, an open-source set of GPU-accelerated ROS packages for building robotics apps with AI agents. The update adds an agent-ready inference library for FoundationPose that speeds up object pose tracking by up to 5.5x. It expands support to ROS Lyrical and Ubuntu 24.04 and adds new skills/workflows plus Jetson platform coverage to move faster from development to on-robot deployment.
Verda, a Helsinki-based AI cloud provider, closed a Series B funding round and reached unicorn valuation as it builds out GPU capacity for AI training and inference. The round raised 189 million dollars (about 161 million euros) and was led by Emergence Capital. The company will use the money to expand data centers, hardware, and its software platform, aiming for more than 250 megawatts in operation by 2027.
Verda raised $189 million to scale its full-stack AI cloud and expand compute capacity. The round was led by Emergence Capital and pushed Verda’s total funding to more than $450 million, valuing it at over $1 billion. Verda will use the money to accelerate product development across its AI cloud, increase inference and multiply its compute capacity over the next year, and expand internationally.
Taiwanese chip and AI experts describe how Taiwan’s semiconductor dominance makes advanced AI chips widely available while Taiwan is largely absent from training the AI models that run on them under pressure from Beijing.
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