A startup asked the FCC to license a data center in orbit. To train AI.
Starcloud's filing, in its own words: "near-constant solar power, radiative cooling, and the ability to scale sizes and power levels not possible on earth."
https://t.co/Za7J5lx3Pr
benchmarked 5 xAI models on 42K regulatory filings before committing to a batch run
reasoning models scored higher confidence but actually hallucinated structure in documents that had none.
for structured extraction: you don't need the model to think, you need it to parse.
Hot take: the space industry's AI trust problem isn't about catching fake filing numbers.
It's about catching fake narratives that connect real ones.
New post on The Downlink → https://t.co/LLQTKItLCv
Cut my GitHub Actions multi-arch Docker build from ~17 min to ~3 min. ~6x faster.
The fix: stop using QEMU emulation. Build arm64 and amd64 natively in parallel, then stitch the manifest in 15 seconds.
Reduced our test & build time from 21m 8s to 3m 23s—an 84% improvement. 🚀
Small optimizations across the pipeline compound fast. Docker layer caching, parallel test execution, and strategic dependency pruning made the difference.
Every minute saved is feedback velocity gained.