3,690 items tracked: 31 reported by two or more outlets, the rest by a single source. Most-corroborated first.
Data sovereignty is becoming an architectural problem as enterprises push artificial intelligence inference toward their most sensitive information.
AI factories run on graphics processing units that cost a fortune and work at blistering speed, yet those chips increasingly sit idle waiting for data.
Across industries, the U.K.
The company unites resources from disparate macOS devices
Self-replicating AI botnets could become feasible on IoT hardware within months, claims the Claude maker, if smaller models get smarter
The next time you vibe-code a custom app with Google's AI Studio, you won't have to connect your phone to a computer to install it.
Americans have big concerns about artificial intelligence, but that hasn’t stopped OpenAI Inc., Nvidia Corp., IBM Corp.
NVIDIA is making the full NVIDIA Run:ai platform available as open source software, giving customers, developers, and ecosystem partners access to...
When Nvidia originally showed off DLSS 5 earlier this year, the technology immediately got branded as gen AI for video games.
96-chip configuration promises seven times its predecessor's token throughput, with production deployments due in 2027
NVIDIA RTX Spark is a new beginning for the PC — a reinvention combining the capabilities of a gaming PC, a creative studio and a personal AI supercomputer into a single superchip.
Voice AI is quickly becoming core infrastructure as people swap screens and clicks for conversations with their devices.
Learn how to run OpenAI GPT-6 Sol, Luna, and Astra on Amazon Bedrock through global cross-Region inference from Singapore, Jakarta, Thailand, Malaysia, and Taipei.
Learn how to deploy one large language model across two GPU nodes on Amazon EKS using the multi-node Ray LLM Deep Learning Containers, with separate prefill and decode nodes behind one OpenAI-compatible endpoint.
Microsoft will make its in-house Azure Maia chips the main AI inference system across its products starting in 2027, deploying them at multi-gigawatt scale.
Just over two weeks before The Register’s Washington dinner with HPE and NVIDIA, the questions on the table are the ones that decide the architecture.
Microsoft is announcing its third-generation Maia in-house AI chip today, designed to be the "primary AI inference system" for Microsoft's products and services.
On Equity, we debate the impact of data center moratoriums and whether the AI industry has a communication problem.
Data from a16z shows a Jevons paradox in the AI market: token prices keep falling, but H100 GPU rental prices hold steady or climb.
The artificial intelligence infrastructure race is no longer just about building faster chips.
Amazon says it will stop using NDAs when negotiating data center deals with local governments, following a similar move from Microsoft earlier this year.
I’m not going to call the bursting of artificial intelligence bubble yet, not with all that money still pouring into every hardware and software company with AI in their pitch decks.
AI inference is fast becoming the workload that decides the economics of the AI boom.
Bitwise determinism makes large-scale pretraining easier to debug, validate, and resume reproducibly.
Commitment comes as GPUzilla prepares to fortify Uncle Sam's arsenal with at least seven AI-optimized supers
AI model training can leave startups managing infrastructure alongside the products they are trying to build.
Nvidia-backed open source startup makes splashy entrance.
Microsoft's Nvidia-powered Surface RTX Spark Dev Box is available for preorder now and is slated to ship in November for just about $6,000.