Amazon Circumvents Gilroy Community Vote for AI Data Center Using 45-Year-Old Rules

Amazon Web Services (AWS) has started construction on a 56-acre AI data center in Gilroy, California, circumventing a community vote by adhering to local zoning rules set 45 years ago. The project, located between a Walmart Supercenter and the Gilroy Premium Outlets, has been in the approval process since 2020, with the public comment period ending in 2024—before data centers became a hot topic nationwide. This has left residents like Rosa Rodriguez locked out of the discussion, despite concerns about drought and environmental impact.
Key Details
- Location: 56-acre farmland in Gilroy, CA, about 30 miles southwest of San Jose.
- Zoning loophole: The site adheres to industrial zoning rules established 45 years ago, which do not require a public vote for projects of this scale.
- Approval timeline: Application started in 2020; permitting was delayed at least one year due to disagreements between Amazon and city officials. The public comment period closed in 2024.
- City position: Gilroy City Mayor Greg Bozzo stated that other similar-scale industrial projects, like a food-distribution center, have been approved without resistance.
- Amazon response: Roger Wehner, AWS VP of economic development, said the site went through a long approval process with public notices and comment periods.
This case highlights how legacy zoning rules can allow large infrastructure projects to bypass modern community engagement. For developers tracking AI data center expansion, this is a precedent that could affect planning and community relations in other regions.
📖 Read the full source: HN LLM Tools
👀 See Also

llama.cpp Q8_0 quantization gets 3.1x speedup on Intel Arc GPUs with SYCL reorder fix
A fix to llama.cpp's SYCL backend brings Q8_0 quantization on Intel Arc GPUs from 21% to 66% of theoretical memory bandwidth, achieving 15.24 tokens/second versus 4.88 tokens/second previously on an Arc Pro B70 with Qwen3.5-27B.
Please Stop Flooding Open Source Projects with AI Slop
A maintainer calls out AI-generated PRs and security reports flooding open source projects, closing typo-fix PRs without comment and urging contributors to care about projects, not just GitHub badges.

The West Forgot How to Build: Defense Supply Chain Collapse and Lessons for Software Engineering
Raytheon had to bring back retired engineers to restart Stinger missile production from 40-year-old paper schematics. The same pattern is now playing out in software, where decades of optimizing for cost have atrophied the talent pipeline and institutional knowledge.

Liquid AI releases LFM2.5-350M model for agentic loops
Liquid AI released LFM2.5-350M, a 350M parameter model trained for reliable data extraction and tool use. It's under 500MB when quantized and outperforms larger models like Qwen3.5-0.8B in most benchmarks while being faster and more memory efficient.