Tech's $380 billion splurge: This quarter's winners and losers of the AI spending boom (www.cnbc.com)

Big tech’s spending spree on AI just accelerated: Amazon, Alphabet, Microsoft and Meta raised capital-expenditure forecasts in their latest earnings, signaling a sustained build-out of AI infrastructure. Standouts include Amazon’s new ~$125B capex target (up from $118B), Google’s boost to $91–93B (from $75–85B), and Microsoft flagging sharp capex growth into fiscal 2026 after capex rose 45% to $64.55B last year (implying a minimum of ~$94B next year before leases). Cloud revenue growth underscores the demand: AWS revenue rose 20% to $33B, Azure grew 40%, and Google Cloud was up 34% to $15.15B. OpenAI’s recently disclosed infrastructure deals—roughly $1 trillion with partners like Nvidia, Oracle and Broadcom—put the scale of commitments into stark relief. For the AI/ML community this matters because hyperscalers are racing to provision compute (chips, datacenters, networking and leases) and cloud services that will underpin large-model training and inference at massive scale. That creates opportunities—more accessible scale, new managed model services, and faster iteration—but also risks: investor wariness, concerns about an AI infrastructure bubble, and real-world resource constraints (power, supply chains). Market reactions were mixed (Amazon and Google up, Microsoft and Meta softer), and analysts warn total capex including leases could hit ~$140B this year—up 58%—spotlighting both the upside for cloud-enabled AI and the financial/operational stresses of funding it.