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Part of the reason for Google’s huge capex plans: It has a $240 billion revenue backlog

Google reported strong earnings yesterday that beat analysts’ expectations. But the thing that caught investors’ attention was Google’s capex plans.

The company spent a whopping $91.4 billion for all of 2025 on capex, but it plans to roughly double that amount in 2026 to between $175 billion and $185 billion.

Why does it need to spend so much? It can’t keep up with demand due to constraints on its compute capacity. Cloud computing demand is surging, and Google simply can’t fulfill all of the orders it has, because it can’t build the data centers and AI infrastructure fast enough.

Alphabet CEO Sundar Pichai was asked on last night’s earnings call what keeps him up at night:

“At this moment, maybe the top question is definitely around compute capacity. All the constraints, be it power, land, supply chain constraints — how do you ramp up to meet this extraordinary demand for this moment, get our investments right for the long term, and do it all in a way that we are driving efficiencies and doing it in a world-class way?”

Demand is so extraordinary that Google has $240 billion in “remaining performance obligations” (RPO, or revenue backlog).

This swelling backlog is not unique to Google. Microsoft just reported $625 billion in RPO, though a big chunk of that was for one customer: OpenAI. After market close today, we will see what Amazon’s RPO backlog looks like. It was $200 billion last quarter.

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Alphabet’s drone delivery startup, Wing, expands service to the Bay Area

Move over Waymo — another one of Alphabet’s “Other Bets” is expanding. Drone delivery company Wing said Monday it’s bringing its “ultra-fast residential drone delivery service” to the Bay Area, where autonomous ride-hailing service Waymo also has a sizable presence.

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Tesla and SpaceX to jointly run “most epic chip-building exercise in history by far”

In the latest instance that Elon Musk views Tesla and SpaceX as effectively one company, the CEO of both announced Saturday that the two firms will join forces on his Terafab project — what Musk says will be “the most epic chip-building exercise in history by far.”

Many of the details mirror what we reported last week, with one major addition: SpaceX will play a leading role.

Terafab, whose location is still under consideration as the facility would be too big to fit on the Giga Texas campus, aims to vertically integrate the entire chipmaking process, from design and fabrication to testing and packaging. The goal is to supply AI chips to Tesla, SpaceX, and its subsidiary xAI, Musk’s AI company, whose suppliers Musk said will be unable to handle their demand in “three or four years.” While Tesla has designed its own chips, it has never manufactured them.

Musk said the facility is intended to produce up to 1 terawatt of compute annually. The plant will manufacture two types of chips: inference chips for Tesla’s Robotaxis and Optimus robots, and custom AI chips intended for space-based applications like solar-powered AI satellites. According to Musk, roughly 80% of the compute will be allocated to space-related uses, with the remaining 20% supporting projects on Earth.

Morgan Stanley has estimated the project could cost Tesla an additional $35 billion to $45 billion in capital expenditure, though now perhaps some of that capex might be shared with SpaceX. Like many of Musk’s ambitions, the project is enormous in scale and will likely to take years to complete — potentially into the end of the decade or beyond.

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Jon Keegan

White House releases AI legislative framework

The White House has released its policy wish list for AI legislation — and what it wants excluded.

Still, the odds of any actual AI regulation getting passed in Congress right now are very slim.

The “National Policy Framework” for AI lays out seven issues that the Trump administration wants to see reflected in any congressional action around AI.

The items listed in the framework include:

  • Child safety protections, age verification, and parental controls for AI.

  • Data center projects voluntarily pay their own way when it comes to power, but incentives should still be encouraged.

  • Copyright laws should allow for training models on copyrighted works, while protecting individuals’ voice and likeness.

  • Free speech should be defended for AI systems, preventing the government from pressuring companies to ban or alter content based on partisan agendas.

  • A light touch to regulation to encourage innovation, and no federal agency to regulate AI.

  • American workers vulnerable to AI job replacement should be retrained and supported.

  • Federal AI rules should preempt any state AI legislation to prevent a patchwork of laws that companies would hate.

The policy list is the latest in a series of proposals from the AI-friendly Trump administration.

The items listed in the framework include:

  • Child safety protections, age verification, and parental controls for AI.

  • Data center projects voluntarily pay their own way when it comes to power, but incentives should still be encouraged.

  • Copyright laws should allow for training models on copyrighted works, while protecting individuals’ voice and likeness.

  • Free speech should be defended for AI systems, preventing the government from pressuring companies to ban or alter content based on partisan agendas.

  • A light touch to regulation to encourage innovation, and no federal agency to regulate AI.

  • American workers vulnerable to AI job replacement should be retrained and supported.

  • Federal AI rules should preempt any state AI legislation to prevent a patchwork of laws that companies would hate.

The policy list is the latest in a series of proposals from the AI-friendly Trump administration.

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