TeraWulf filed three Google backstop agreements for Anthropic's approximately $19 billion, 401 MW lease at its Justified data campus and a definitive Fluor engineering, procurement and construction agreement. The credit support becomes effective by data-hall phase, with deliveries expected from late 2027 through the second quarter of 2028.
Why it matters: The backstops make a very large future AI-infrastructure lease more financeable and show how hyperscaler credit is being used to underwrite capacity for a frontier-model developer before the campus is operating.
Larsen & Toubro said subsidiary LTN Compute secured a 100–150 billion rupee order from Together AI for an AI factory at the Vyoma.AI Chennai campus using 10,000 NVIDIA B300 chips for inference, fine-tuning, and training.
Why it matters: The contract is a large, dated signal of sovereign AI capacity moving from strategy into procurement, but not yet delivered compute.
Google DeepMind, Google Cloud, Faculty, and UK public-sector partners announced a prototype intended to help planning officers review applications, with a stated goal of cutting processing time by 50%.
Why it matters: This is a concrete attempt to apply AI to a document-heavy public workflow with an auditable human decision at the end.
OpenAI announced five new U.S. Stargate data-center sites with Oracle and SoftBank, representing up to 5.5 gigawatts of potential capacity across the selected locations.
Why it matters: Frontier compute expansion was becoming geographically distributed and tied to local power systems, permitting, construction, and community impact rather than one cloud region.
OpenAI announced an agreement with Oracle to develop 4.5 gigawatts of additional U.S. data-center capacity, taking the stated Stargate pipeline with the Abilene site above five gigawatts.
Why it matters: Frontier-model competition became a power, land, construction, networking, and financing problem as much as a model-design problem.
OpenAI, SoftBank, Oracle, and MGX announced Stargate as a new company intending to invest $500 billion over four years in U.S. AI infrastructure, with $100 billion described as beginning immediately and an initial Texas buildout underway.
Why it matters: Frontier-model competition was becoming a power, land, networking, construction, and capital-allocation problem. It also concentrated the supply chain around a small group of model, cloud, and chip partners.