Economics & Capacity

I went looking for sustained-load benchmarks comparing MoE and Dense coding models on consumer GPUs. Not demo bursts on a Mac Mini — sustained autoregressive generation on real coding tasks, where architecture and interconnect are the only variables. I found plenty of one-shot numbers. Nobody had published the comparison that matters: same hardware, same quantization, same inference engine, MoE versus Dense, across GPU configurations. Methodology visible. Numbers verifiable. So I ran the tests. Dual RTX 3090s with NVLink, custom liquid cooling, a 6 kW isolation transformer feeding a double-conversion UPS. Not elegant, but thermally and electrically honest — sustained inference loads without throttling, no measurement fiction. The hardware details are below. ...

The Concorde burned one ton of fuel per passenger to cross the Atlantic. One hundred seats. Three and a half hours. Mach 2. The most advanced commercial aircraft ever built — and every engineer who saw it wanted to believe it was the future. The 747 did the same crossing in seven hours. Four hundred seats. A quarter of the fuel per passenger. No afterburners. No sonic boom. No government subsidies keeping it alive. ...

Context got commoditized. Translation is next. When my company’s acquisition closed in 2024, I thought about pursuing a psychology degree in the US. The impulse was the same one that drives URE: wanting to understand how things are wired under the hood. My wife shut it down—“Really? You know that’s not going to work”—and she was right, though neither of us fully understood why at the time. What I was actually chasing wasn’t psychology. It was context. ...

I see people everywhere anxious about whether AI will disrupt their jobs, their industries, their lives. I’ve always approached this with calm. Not indifference—calm. The future rarely sends advance notice, but it is always arriving. This isn’t news. It’s the human condition. A few years ago, I attended a keynote by Michio Kaku where he framed—perfectly, for me—the relationship between humanity and technological change. What follows is my version. I can’t claim novelty, and I’m not a domain expert in sociology or economics. I’m an infrastructure builder observing the same pattern from the inside. ...

A few years ago, I was having dinner with the Americas VP of a European energy supermajor — one of those companies that extracts oil from war zones, negotiates with regimes that don’t appear on polite lists, and operates in places where “political risk” means your assets might get nationalized or your personnel kidnapped. Seventy-plus countries. Active operations in Libya, Nigeria, Angola, Myanmar, Yemen. The kinds of places where security briefings come before breakfast. ...

In 2015, I did what seemed like the mature thing to do. I created a Production Engineering department. My college foundation was production engineering. I was a true believer: if we formalized standards and assigned a dedicated group to own operational rigor, the organization would naturally converge toward consistency. The mandate: Create SOPs. Define standards. Reduce variance. Improve reliability. On paper, it was textbook. In practice, it was a slow-motion collision with reality. ...

I’m currently working on the design of a framework for GPU fleet management. We’re living in a crowded data center reality where everybody wants “hero” compute — dense GPUs, fast networking, and delivery that’s closer to the edge. We’re in a land-grab phase where every business wants to be everywhere, but most teams are discovering the same thing: buying GPUs is the easy part. Operating them as a coherent fleet is the hard part. ...

Atlas is a single pane of glass for multi-cloud cost visibility. This post documents the pipeline: ingestion, streaming, storage, query, forecasting, and visualization.

Traditional internet architecture solved latency with caching. Static content, images, JavaScript bundles—all pushed to edge nodes milliseconds from users. CDNs achieve 95-99% cache hit rates. The compute stays centralized; the content moves to the edge. AI breaks this model completely. Every inference requires real GPU cycles. You can’t cache a conversation. You can’t pre-compute a response to a question that hasn’t been asked. The token that completes a sentence depends on every token before it. ...