Data Gravity
Chris ZeoliQuantitative analysis of the infrastructure, data, and security systems powering AI—written for the founders and operators building them and the investors funding them.
| Platform |  | Pricing | Only free issues | Publishes | Weekly |
|---|---|---|---|---|---|
| Issues | 71 | Founded | 4 years ago | Last Issue | 9 days ago |
| Active | |||||
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datagravity.devLatest Issues
Light, Radio, and the Race to Replace Copper: Interconnects in the AI Era
Thesis
The binding constraint on frontier AI has shifted. Through 2023 it was accelerator supply. By 2026 it is the interconnect — and “interconnect” now spans three distinct distance scales at once: chip-to-memory (millimeters), GPU-to...
Google's TPU Supply Chain
Google’s Tensor Processing Unit program is no longer a side project to keep GPU costs down. It is the structural foundation of how Google intends to own AI compute economics for the next decade. The signal most investors missed: in 2026, Al...
600 kW Per Rack: The AI Power Crisis Reshaping Electrical Infrastructure
TL;DR — Five things to know
AI racks go from 120 kW today to 600 kW by 2027. Power infrastructure value per rack jumps from $36K to $398K+ — more than 10× baseline. This is not incremental.
The architecture shifts c...
The Memory Triopoly
We’ve been talking a lot about memory lately — from KV Cache dynamics across prefill and decode to memory itself as the structural bottleneck in AI compute. The constraint is no longer raw FLOPS. It is the ability to move bytes in and out o...
The Chip Testing Bottleneck
The economics of testing a leading-edge AI accelerator look almost nothing like testing a mobile SoC. A typical 5nm-class smartphone SoC clears the tester in roughly 30–60 seconds. A Blackwell-class AI accelerator with two reticle-limited d...
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Authors
The writers behind this newsletter.
Partner @ Wing investing in AI infra, data and cyber.
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