Google adds CNN and Reach to its AI licensing deals as USA Today Co sues OpenAI for $250M. Terms, lawsuit details and publisher implications.
ASML says EUV lithography supply for 2027 and 2028 will fall short of AI demand, as the Daily Brief tracks Arm, Meta, FTC and Waymo news.
Venture Global plans up to 10 GW of off-grid gas power for AI data centers, with first power targeted for late 2028 or early 2029.
London robotaxi rollout stalls as TfL guidance is pending, drivers protest and the London Assembly seeks fleet caps and TfL oversight.
Boston Dynamics says Atlas humanoid robot now takes a day to build and targets one hour by 2027, ahead of Hyundai factory rollout in 2028.
Accenture now centrally funds only $29 per employee per month for Claude, with overage charged to project budgets. Details and cost implications.
This week's AI business roundup: AI data center power limits, Anthropic and OpenAI revenue and compute costs, enterprise trust gaps and EU AI liability.
Six AI funding deals covered this period, including TypeSafe AI's $870M round at a $7.5B valuation, LS Power's $6B fund and Firmus's scrapped listing.
Microsoft announced the Maia 300 AI inference chip, with multi-gigawatt Azure Maia deployments starting in 2027. Customer pricing is not yet disclosed.
AEP plans a $4B, 702 MW Wyoming fuel-cell plant to supply Google under a 20-year PPA. Who carries the stranded-asset and demand risk?
Agility Robotics SPAC clears SEC review, with a shareholder vote set for November 2. The $2.5B valuation rests on $1.8M in 2025 sales.
IREN shares rose, then faded, on a report of an Anthropic cloud deal. Neither IREN nor Anthropic has confirmed the arrangement.
Portland proposes Portland robotaxi rules capping driverless taxis at 225 a year, 75 per company, with 50,000 local miles required before fares.
Private credit lenders finance AI data centers with chip-backed loans, but chips depreciate faster than the debt. See the collateral risk for neoclouds.
Meta scrapped planned AI-driven job cuts after staff spent growing time fixing AI errors. Analysis of the hidden cleanup costs behind pulling back on AI.
