AI is eight layers. Most coverage reads only the top one. Strata maps all of them, from the power station at the bottom to the agent at the top, and every number on this site carries a source and a confidence label.
The layers
Band Rules and society: Laws, courts, export controls, and whether your neighbours will let you build.
L6 Applications and agents: The products people actually use. Coding assistants, support bots, agents that run for hours.
L5 Tooling and infrastructure: The plumbing between a model and a product. Serving, retrieval, agent protocols, evaluation.
L4 Models: The labs, their releases, and what a million words of output costs you.
L3 Iron and cloud: Servers, networks, and the companies that rent them to you by the hour.
L2 Silicon: The chips. Processors that do the maths, and the memory that feeds them.
L1 Power and land: Electricity, land, water, permits. Nothing above this exists without it.
Band Money: Who is paying, and with whose balance sheet. Cuts through every layer.
Latest
Michigan regulators approve a 20-year Google data-center power deal with DTE, with up to 1,600 megawatts of new renewables
Michigan's state utility regulator approved a new kind of power contract between DTE Electric, the state's largest utility, and Google for a data center Google is building in Wayne County. The deal runs for 20 years, four times longer than the 5-year contracts regulators normally require, and commits Google to pay for DTE to build up to 1,600 megawatts of solar and wind power plus 480 megawatts of battery storage. DTE says the arrangement will save its other customers about $1.7 billion, though that number comes from DTE's own filing to regulators, not an independent check. The data center is expected to start drawing power in December 2027. For everyday DTE customers in Michigan, the point of the deal is that Google, not them, pays for the new power plants built for its data center.
Instinct, a startup building a personal AI assistant, raised another $1 billion from investors Sequoia Capital, Benchmark Capital, and Coatue, according to the company's own announcement. Unlike many large funding rounds, none of the three is named as the lead investor; the release lists them as co-investors. The new round values Instinct at $10 billion, though that number appears only in the announcement's headline, not spelled out again in the body text. This is new money for a consumer AI product most people have not used yet, not a sign the industry overall is changing, but it is one of the larger single checks written for an AI startup this week.
Enerflex, a company that builds power equipment, announced a contract to supply approximately 450 megawatts of natural-gas power generation directly at an undisclosed data center site in North America. The company said it will spend about $15 million this year and about $85 million more, mostly in 2027, to expand its ability to build this kind of equipment. The customer was not named. This is a reminder that much of the new power being built for AI data centers today is still gas, not renewables, because gas turbines can be installed faster than waiting for grid upgrades.
Fourteen Taiwanese banks, led by CTBC Bank, together lent NT$14.05 billion, about $445 million, to GMI Cloud to help build an AI data center in Taoyuan. GMI Cloud's own announcement of its wider $668 million financing round independently confirms the $445 million figure. Chinatimes and UDN name the other 13 banks in the syndicate, but their account of the 2.5-times oversubscription and the Taiwan-first claim traces to the same CTBC-arranged release as CNA's, not to separate reporting. For Taiwan, it is a sign that local banks, not just foreign investors, now see AI infrastructure as a safe enough bet to lend against directly.
EliseAI, which sells AI software that answers phone calls and schedules tasks for apartment leasing offices and healthcare practices, raised $350 million at a $4 billion valuation. The round was led by Andreessen Horowitz and Bessemer Venture Partners, with Ontario Teachers' Pension Plan and others also putting in money. This is the kind of AI that is already answering real phone calls for property managers and medical offices today, not a research project, so if you've called a leasing office recently, there's a decent chance you spoke to software like this without knowing it.
GMI Cloud, a company that rents out AI computing power, raised $223 million in equity and a separate $445 million credit facility led by Taiwan's CTBC Bank, for a combined $668 million. The company said its contracted annual revenue has grown more than ninefold since the end of 2025. Most of the new money is debt, not equity, which means GMI Cloud is betting it can earn enough from renting out chips to pay the loan back. It's a sign that lenders, not just venture investors, are now willing to bankroll AI computing buildouts directly.
Nvidia is launching a new, lower-memory version of its DGX Spark desktop computer, a small machine meant for running AI models at a desk rather than in a data center. The 64GB version starts at $4,999 and goes on sale October 23 through PC makers including Dell, HP, and Asus. Two of these machines can be linked together to match the memory of the original, more expensive model. This gives developers and small businesses a cheaper way to experiment with AI models at home instead of paying for cloud computing time.
A new coalition of labor unions and data-center companies, including OpenAI, CoreWeave, SoftBank, and Blackstone, launched what it calls the first nationwide partnership between construction unions and the data-center industry. The group says it wants to set shared standards for building data centers responsibly; an IBEW union leader warned that blanket bans on data centers would cost construction jobs. The announcement names no dollar figure or specific commitment, so for now this is a statement of intent between labor and industry, not a concrete rule change; whether it changes anything for communities near data centers depends on standards the group has not yet published.
On the same September 30 earnings call where Micron reported record revenue, already covered here, the company's own market outlook added a specific extension: supply and demand in calendar 2027 and 2028 will stay much tighter than in 2026, and Micron said it does not have line of sight to when that balance returns. This is Micron's own quarterly disclosure, not a third-party forecast, confirming in the company's own words what outside analysts had only predicted. Micron makes the memory chips used in AI servers as well as ordinary phones and laptops, so a longer shortage points toward memory prices, and potentially the price of phones, laptops, and other electronics, staying higher for longer.
We Energies and Oracle agreed on a deal meant to save the utility's Wisconsin customers about $300 million in fuel costs tied to the Point Beach nuclear plant. The agreement is not yet final, it still needs to go to the Wisconsin Public Service Commission for review in the coming months. Oracle is building a large data center in the state as part of its 'Project Lighthouse' development. If regulators approve it, the deal means Oracle, rather than ordinary ratepayers, absorbs more of the cost increase tied to powering the grid the data center relies on.
Anthropic, the company behind the Claude AI models, announced a program called Claude Frontier Academy, backed by a $100 million commitment, aiming to train 10,000 'Frontier Deployed Engineers' by the end of 2027. These are specialists meant to help other companies actually put AI systems to work inside their own operations, not people who build AI models themselves. Anthropic said more than 175,000 people across 46,000 firms have already earned a Claude certification through its existing partner program. If this succeeds, the practical effect for most people is indirect: more trained specialists available to help your employer actually deploy AI tools, rather than leaving that work undone or outsourced to whoever happens to understand the software.
A syndicate of Taiwanese commercial banks, not foreign venture capital, financed GMI Cloud's AI data center buildout, and the borrower's own numbers confirm how much.
Strata, the whole AI stack, explained simply. Every number carries a source and a confidence label.