Tech
Nvidia conference with Jensen Huang
Nvidia CEO Jensen Huang delivers a keynote address during the Nvidia GPU Technology Conference in March 2024 (Justin Sullivan/Getty Images)

More than a third of Nvidia’s revenue comes from three customers. That’s increasingly precarious.

A huge chunk of revenue is tied to three mystery companies that are likely all similar, all spending money like they never have before, and all trying to achieve the same perhaps unachievable outcome of super-profitable AI. What could go wrong?

An interesting reveal from Nvidia’s earnings report yesterday is that 34% of the company’s bonkers $130 billion revenue line last year came from just three customers.

We don’t definitively know who they are because they’re cryptically referred to as “Customers A, B, and C” in Nvidia’s annual report. But it’s a pretty safe bet to say, given who has boasted about capital spending plans and hoarding Nvidia chips, that they’re some of the biggest tech companies on the planet. 

Those customers, part of the vaunted “Magnificent 7” that investors love to pile into, have been shouting some mind-blowing 2025 capex forecasts from the rooftops: $100 billion for Amazon, $80 billion for Microsoft, up to $65 billion for Meta, and the list goes on.

That bodes well in the immediacy for Nvidia — the companies that have been driving its insane growth are saying the firehose will likely remain on this year. 

But Nvidia’s revenue line is getting more concentrated. In fiscal 2023, no Nvidia customer accounted for even 10% of its individual revenue. In 2024, one customer did, and it made up 13% of the top line. This year, three companies topped that 10% threshold: Customers A, B, and C were responsible for 12%, 11%, and 11%, respectively, of all Nvidia revenue.

Is that sustainable or healthy? Think about it: when more and more of your revenue — and thus the profits that drive your stock price — are tied up in fewer customers, and those customers are spending exorbitant amounts of money like they never have before, things could get hairy.

For example, Meta’s anticipated $75 billion of capex in 2025 sounds great if you’re one of the companies it’s writing checks to. Capex, of course, is on the balance sheet and doesn’t flow cleanly through to the income statement. But indulge me the unorthodox financial metric for a second and consider: in its entire life as a public company, Meta has generated $286 billion of profit and has racked up $177 billion of capex. That’s a capex-to-income ratio of 62%.

This year, Wall Street expects Meta to generate $64.9 billion of profit, according to FactSet, which would be its most profitable year ever. But the company says it will dole out $60 billion to $65 billion — roughly that entire year’s worth of profit — on capital spending. Capex-to-income ratio? Right around 100%.

The profits will still be there, but I’m trying to put into perspective the raw size of these spending plans. And of course I should say we don’t know for sure whether Meta is one of the big three customers Nvidia mentioned. But even if it’s not, it’s likely spending in a similar way.

While these types of companies — including, presumably, Customers A, B, and C — are spending boatloads of money to make AI happen, there are still questions about whether the technology will generate significant financial benefits that come anywhere close to the amount of money being invested to develop it. Simultaneously, there’s seemingly a race to the bottom happening, as companies like DeepSeek develop ultracheap AI and the general public seems to coalesce on the opinion that cheaper is “good enough.”

In the tech world, things can change quickly. It was only October 2021 when Facebook changed its name to Meta and Mark Zuckerberg wrote in his founder’s letter, “From now on, we will be metaverse-first, not Facebook-first.” On the company’s most recent earnings call, “metaverse” was mentioned twice. “Facebook” was mentioned 14 times. 

Having a revenue base made up largely of a few big spenders has historically not been a great business idea. Now think about more than one-third of Nvidia’s revenue being made up of spending by similar companies, with similar risk profiles, trying to achieve similar transformative AI outcomes that they hope will be extremely profitable. 

I’m not saying the profits won’t come. But what happens if they don’t? 

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Google testing Gemini app for Mac, aims to compete with Claude Cowork and Codex

Bloomberg reports that Google is testing a new version of its Gemini AI app that runs on Apple’s Mac computers.

Currently both OpenAI’s Codex and Anthropic’s Claude have Mac apps, which allow for deeper AI automation with files on the computer.

Google is testing a feature called Desktop Intelligence, which grants Gemini access to the items on the user’s screen, according to the report. The app is currently in beta testing.

Google is testing a feature called Desktop Intelligence, which grants Gemini access to the items on the user’s screen, according to the report. The app is currently in beta testing.

tech

Bezos seeks $100 billion for AI-enhanced manufacturing fund, WSJ reports

Amazon founder Jeff Bezos is seeking to raise a $100 billion fund that would purchase manufacturing companies and use AI to automate their work processes, according to a new report from The Wall Street Journal.

The fund would use technology from Project Prometheus, where Bezos was recently named co-CEO. The startup aims to apply the latest generative-AI breakthroughs to reinvent industrial manufacturing.

The $100 billion fund would be used to buy existing manufacturing businesses to transform, per the report.

Bezos has reportedly met with the heads of sovereign wealth funds in the Middle East and recently traveled to Singapore as part of the fundraising effort.

The $100 billion fund would be used to buy existing manufacturing businesses to transform, per the report.

Bezos has reportedly met with the heads of sovereign wealth funds in the Middle East and recently traveled to Singapore as part of the fundraising effort.

tech

OpenAI acquires Astral, adding talent to Codex team

OpenAI has acquired open-source Python tool developer Astral, bringing aboard additional coding talent for its Codex team.

The company said the acquisition will help Codex “expand beyond coding” by helping address a wider range of development tasks, such as planning, testing, and code maintenance.

OpenAI said Codex has seen “3x user growth and 5x usage increase” since the start of 2026, and has over 2 million weekly active users.

Software development is emerging as one of the key battlegrounds where OpenAI is competing for market share with Anthropic, which has been enjoying success with its Claude Code product.

OpenAI said it will continue to support Astral’s open-source software projects.

OpenAI said Codex has seen “3x user growth and 5x usage increase” since the start of 2026, and has over 2 million weekly active users.

Software development is emerging as one of the key battlegrounds where OpenAI is competing for market share with Anthropic, which has been enjoying success with its Claude Code product.

OpenAI said it will continue to support Astral’s open-source software projects.

tech

Elon Musk gives an estimate for Tesla’s AI6 chip timeline... while the AI5 is still unfinished

Tesla CEO Elon Musk said yesterday that the company’s AI6 chip could, with “some luck and acceleration using AI,” be finalized and sent to manufacturing by December. For those paying attention, Tesla hasn’t confirmed that its previous chip, the AI5, has reached tape-out, with Musk saying only that the design is in “good shape” and “almost done.” Still, Musk is already talking about subsequent chips AI6, AI7, AI8, and beyond.

Here’s a roundup of when these chips are expected, what they’re supposed to do, and what Musk himself has said about them.

While the AI5 and AI6 will be made by TSMC and Samsung, respectively, Musk has said Tesla eventually aims to manufacture its future AI chips at Tesla’s upcoming Terafab factory in Austin.

tech

NHTSA expands Tesla FSD probe, focusing on whether system can detect when cameras can’t see the road

The National Highway Traffic Safety Administration said it is expanding its probe into Tesla’s Full Self-Driving system into an engineering analysis covering about 3.2 million Teslas, a majority of its vehicles that are on the road in the US, Reuters reports.

The agency is focusing on Tesla’s “degradation detection system,” which is meant to recognize when its camera-based technology cannot reliably perceive the road and prompt drivers to intervene:

“Available incident data raise concerns that Tesla’s degradation detection system, both as originally deployed and later updated, fails to detect and/or warn the driver appropriately under degraded visibility conditions such as glare and airborne obscurants. In the crashes that ODI has reviewed, the system did not detect common roadway conditions that impaired camera visibility and/or provide alerts when camera performance had deteriorated until immediately before the crash occurred.”

Tesla CEO Elon Musk has long argued that the company’s self-driving approach does not require the expensive lidar sensors used by rivals such as Waymo.

The agency is focusing on Tesla’s “degradation detection system,” which is meant to recognize when its camera-based technology cannot reliably perceive the road and prompt drivers to intervene:

“Available incident data raise concerns that Tesla’s degradation detection system, both as originally deployed and later updated, fails to detect and/or warn the driver appropriately under degraded visibility conditions such as glare and airborne obscurants. In the crashes that ODI has reviewed, the system did not detect common roadway conditions that impaired camera visibility and/or provide alerts when camera performance had deteriorated until immediately before the crash occurred.”

Tesla CEO Elon Musk has long argued that the company’s self-driving approach does not require the expensive lidar sensors used by rivals such as Waymo.

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