intelligence_src_33e452677074d4c3bd
- Source-provided label
- Publisher RSS metadata
- Evidence class
- mentioned in report
- Confidence
- Not reported
- Observed
- Oct 10, 2026 14:00 UTC
- Retrieved
- Oct 13, 2026 08:33 UTC
The basement of Gary Flake’s contemporary home in a quiet neighborhood in Bellevue, Wash., is furnished with everything you’d expect in a multipurpose man cave. There’s a cozy-looking couch situated between a large screen and a digital projector, a Peloton treadmill and a rowing machine. The real showpiece of the space, however, is a custom computer that resembles an oversized erector set, one with seven large Nvidia graphics processing units dangling from its frame. Flake, a former Microsoft executive and startup founder, built the computer to train custom AI models on terabytes of data from electroencephalograms, the tests that measure electrical activity in the brain—part of a startup project he has since moved on from. To train his AI models, Flake could have paid a cloud service to train them on the industrial-strength GPUs inside their data centers, but he said it was far cheaper to assemble his own machine out of discounted parts (total cost: under $6,000) than to fork over fees to Amazon Web Services or Microsoft every month. That’s true even when including the $10,000 to $20,000 he spent for electrical upgrades and a new HVAC system he bought to keep his basement cool while his AI computer throws off a lot of heat. “I want to own,” said Flake, who plans to begin using the computer again for a new AI project in the coming months. “I don’t want to rent.”
51b6f3b726a58fbe718cf3e62c04b1156c1d2c9ef6c47cdd15bc4943d39b0022Network indicators are visibly defanged. This page does not make them clickable or send them to another service.
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