Airy buying intent

Nvidia is putting data centers on the walls of houses. 16 Blackwell GPUs, 4 AMD EPYC CPUs, and 3TB of RAM mounted outside your home like an HVAC unit. Span, a California startup that started with smart electrical panels in 2018, is now building mini data center nodes called XFRA units. They mount on the side of residential homes and small businesses. They tap unused electrical capacity on local grids. AI cloud providers connect to the network remotely and run inference workloads. PulteGroup, one of the largest homebuilders in the US, is already installing them in newly built communities. The math Span is pitching: 8,000 of these units can be deployed 6x faster and at one-fifth the cost of building a comparable 100 MW centralized data center. Homeowners get a flat fee for power and Wi-Fi, plus compensation based on how much compute and energy the network uses. This is the data center version of distributed solar. Instead of building one massive facility that needs its own power plant, gas turbines, and a seven-year grid interconnection queue, you spread the compute across thousands of homes that are already connected to the grid. The parallels to energy are striking. Centralized power plants had the same problems data centers have now: hard to site, expensive to build, community opposition, grid bottleneck. Distributed solar solved many of those by putting generation on rooftops. Distributed compute could do the same by putting processing on house walls. Homeowners become infrastructure. Your house generates solar during the day, runs AI inference with the excess capacity, stores energy in a battery at night, and earns revenue from all three. Whether this actually works at scale depends on questions that haven't been answered yet. Latency for distributed inference. Heat management on a residential wall. Noise. Maintenance. What happens when the homeowner's electrical demand spikes and the compute needs power at the same time. But the concept is worth watching closely. The data center industry's biggest constraint is power and permitting. Thousands of homes with spare electrical capacity and existing grid connections bypass both constraints simultaneously.

I know. Musk is complicated. For a lot of people, he's gone from hero to villain over the past years. I get it. I have my own strong feelings about his politics and his role in DOGE. But the machine that is Tesla keeps doing important work. Tesla built a lithium refinery in Texas that doesn't use acid. That sounds like a small detail. It's a massive one. Traditional lithium refining uses sulfuric acid. It produces toxic waste streams. It's energy intensive. And it's almost entirely done in China, which processes roughly 65% of the world's lithium. Tesla's Corpus Christi refinery takes a different approach. No acid. Water recycled throughout production, treated and cleaned on site. The byproducts are safe enough to be reused. And it feeds directly into their battery supply chain. This is vertical integration applied to critical minerals. The same playbook Google used when it bought Intersect Power for $4.7 billion to own its energy supply. If you can't rely on the supply chain, become the supply chain. The interesting question isn't whether the refinery works. It's whether it scales. Right now the US mines lithium, ships it to China for processing, then imports it back as battery-grade material. The round trip adds cost, time, carbon, and geopolitical risk at every step. If Tesla can prove that acid-free refining works at commercial scale with competitive economics, the playbook becomes available to everyone. Domestic mining to domestic refining to domestic battery production. One refinery doesn't change the supply chain. But one refinery that works changes the math on building the next ten.

Medium​Gliffy vs. Cloudairy: Is the Atlassian Default Tool Slowing Your Agile Team Down? | by Cloudairy | Medium Sign up Cloudairy Diagram # ​Gliffy vs. Cloudairy: Is the Atlassian Default Tool Slowing Your Agile Team Down? 11 min read Feb 24, 2026 -- Share Press enter or click to view image in full size ## ​Introduction: The “Default” Trap Nothing can kill engineering speed more than this phrase

​Eraser.io vs. Cloudairy: Do You Need a “Doc Tool” or a “Diagram Engine”? | by Cloudairy | Feb, 2026 | Medium Sign in Medium Logo Write Search Sign up Sign in # ​Eraser.io vs. Cloudairy: Do You Need a “Doc Tool” or a “Diagram Engine”? Cloudairy 13 min read Feb 19, 2026 -- Listen Share Press enter or click to view image in full size ## The “Docs vs. Visuals” Dilemma There is no lack of options in t

MediumMermaid.js vs. Cloudairy: Why Write Code When You Can Just Prompt? | by Cloudairy | Medium Sign up # Mermaid.js vs. Cloudairy: Why Write Code When You Can Just Prompt? 10 min read Feb 17, 2026 -- Share Press enter or click to view image in full size ## The “Code-First” Revolution If you are a developer, you probably hate dragging boxes in Visio. There is a particular kind of pain in aligning