Browsing Tag
NVIDIA
16 posts
NVIDIA chips, software, AI infrastructure, and developer platforms.
NVIDIA’s AI Cloud Deals Turn GPUs Into a Revenue-Share Business
NVIDIA’s July 1 revenue-sharing and credit-support model gives AI cloud partners a new way to finance large GPU deployments, while giving NVIDIA a usage-linked cut of supported cloud revenue. Sharon AI and Firmus are the first test cases, with plans for up to 210,000 GPUs across Australia and Indonesia.
Micron’s Hiroshima HBM Expansion Shows AI Memory Is the Next Supply Fight
Micron has broken ground on a roughly $9.3 billion Hiroshima expansion that will produce high-bandwidth memory for AI processors, with shipments expected around summer 2028. The timing shows why memory, not just GPUs, has become a strategic bottleneck for AI infrastructure buyers.
Claude Science Turns Research AI Into a Lab Workflow Layer
Anthropic’s Claude Science beta gives researchers an AI workbench for literature review, code, compute jobs, scientific figures, and lab-specific agents. The launch matters because it treats AI for science less like a single model race and more like a workflow layer that has to connect databases, HPC systems, NVIDIA BioNeMo tools, and reproducible artifacts.
Verkada and NVIDIA Push Physical AI Deeper Into Security Cameras
Verkada says NVIDIA is now both an investor and technical collaborator as it scales physical AI across more than 2.4 million devices. The deal turns enterprise security cameras into a clearer test case for AI video search, synthetic training data, and governance around real-world monitoring.
Etched’s $1B Sohu Backlog Turns AI Inference Into the Next Chip Fight
Etched says it has raised $800 million, signed more than $1 billion in customer contracts, and started production of its Sohu-based inference racks. The startup’s transformer-specialized chip is a serious bet that AI’s next hardware fight will be won on serving models, not just training them.
Nvidia’s Firmus Deal Turns Batam Into an AI Factory Test Case
Firmus will build a 360 MW Nvidia DSX AI factory campus in Batam, Indonesia, with access to as many as 170,000 Nvidia accelerators. The deal shows how AI infrastructure is shifting from one-off data centers toward financed cloud capacity for AI-native companies.
OpenAI’s Jalapeño Chip Puts Inference Costs at the Center of the AI Race
OpenAI and Broadcom unveiled Jalapeño, OpenAI’s first custom inference accelerator for large language models. The chip is less about replacing Nvidia overnight than controlling the cost, latency, and supply of the compute that runs products like ChatGPT, Codex, and the API.
Qualcomm’s Modular Deal Is a $3.9 Billion Bet on AI Software Portability
Qualcomm agreed to acquire Modular in a nearly $4 billion stock deal, giving its AI data center push a software layer built around portable model deployment. The move is aimed at a practical bottleneck in AI infrastructure: making models run efficiently across CPUs, GPUs, NPUs, and custom accelerators without locking developers into one hardware stack.
NVIDIA Rubin Pushes AI Data Centers Toward Hotter, Drier Cooling
NVIDIA says its Rubin-generation AI infrastructure can run fully liquid-cooled servers with 45°C coolant, cutting facility cooling water use from conventional tower-based levels to near zero in favorable climates. The design is a real shift for AI factories, but it does not erase the water tied to power generation, chip manufacturing, or local data center siting fights.
Groq’s $650M Raise Makes AI Inference the New Cloud Fight
Groq raised $650 million to expand its AI inference cloud, with 13 data centers, more than five million developers, NVIDIA LPX integration, and a 200 MW capacity target by the end of 2027. The deal shows why serving AI models is becoming its own infrastructure market, separate from the training race.