Digital Ads
Written by
Beth Kindig
Founder, CEO and Lead Technology Analyst
Published: February 20, 2020
Last Updated: February 20, 2020
INTRODUCTION:The announcement that Facebook is killing off web supply on Audience Network is actually quite important. This is because the story is changing. You can ex...
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Since 2022, Big Tech capex has been the clearest barometer of AI demand. But the market’s reaction to Google’s latest earnings shows investors are questioning how long that spending can last. While the market frets over hyperscalers’ cash flows, a second wave of AI infrastructure spending has quietly emerged, driven by enterprises and neocloud customers.
In April, there was a major shift in the AI accelerator market, and for once, it didn’t come from Nvidia. Six months later, merchant TPUs are moving from announcement to commercial execution, with Google recognizing its first revenue from TPU systems in Q2 (from a small base). Last quarter, Cloud revenue growth accelerated to 82% for $24.8 billion, compared to $22.5 billion expected. In addition, new details around the TPU 8t show that Google’s threat to Nvidia is not limited to inference. At the time, we pointed out that Google may be one of Nvidia’s strongest AI challengers, as Big Tech is closest to the problems that accelerators must solve. The problem that Google is prioritizing is lower cost per token, with token economics becoming a predominant concern as AI spending is pushing Big Tech’s free cash flows into the red. Below, we discuss two reasons why Google’s AI story is about to change, not from advancements in AI software, but by going after one of the most profitable hardware businesses the tech industry has ever seen.
AI-related debt reached $466 billion through September 2026, more than four times last year’s pace. We break down who is borrowing, the three ways new AI chip deals are being structured, and where interest costs land across Nvidia, Oracle, CoreWeave, Broadcom and Big Tech.
