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title: Where Do Frontier AI Models Actually Keep Their Data?
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# Where Do Frontier AI Models Actually Keep Their Data?

**[Medium](https://daily.dev/sources/medium_js)** · 13 min read · 1 upvotes · 0 comments

## Summary

Frontier AI models touch four distinct data categories: training corpora (petabyte-scale, private), model weights (hundreds of GB to ~2 TB), inference logs (your prompts, retained longer than policies suggest), and enterprise retrieval data. All of it concentrates in a handful of hyperscale data centers financed increasingly by debt. Courts have already ordered OpenAI to preserve and produce chat logs users thought were deleted. Over 100 US municipalities have imposed moratoriums on new data centers, and the BIS has flagged AI capex as a financial stability risk. The EU AI Act's Article 53 now requires training data summaries, but the entire compliance chain rests on trust since no independent verification exists. Decentralized storage networks like Filecoin, Arweave, and Walrus don't train models but can provide cryptographic custody and verifiability for datasets, checkpoints, and audit logs — turning compliance claims into checkable receipts. The piece also promotes Xandeum, a storage layer readable by smart contracts, currently at 110 nodes and 355 TB capacity with minimal actual usage.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://medium.com/@abdoubada/where-do-frontier-ai-models-actually-keep-their-data-6ec855d23213>

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