惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
V
V2EX
WordPress大学
WordPress大学
U
Unit 42
I
InfoQ
A
About on SuperTechFans
宝玉的分享
宝玉的分享
J
Java Code Geeks
博客园 - 司徒正美
爱范儿
爱范儿
Engineering at Meta
Engineering at Meta
G
Google Developers Blog
人人都是产品经理
人人都是产品经理
小众软件
小众软件
Microsoft Security Blog
Microsoft Security Blog
L
LangChain Blog
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
Hugging Face - Blog
Hugging Face - Blog
H
Hackread – Cybersecurity News, Data Breaches, AI and More
aimingoo的专栏
aimingoo的专栏
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
Last Week in AI
Last Week in AI
腾讯CDC
Recent Announcements
Recent Announcements

Hacker News - Newest: "AI"

AI can't read an investor deck AI as an attorney? Student uses ChatGPT, Gemini to sue UW over alleged racial discrimination Hacking MCP Servers in AI Systems – The Rug Pull: Tool Changes After Approval GitHub - MeepCastana/KubeezCut: Free Web based video editor Can AI judge journalism? A Thiel-backed startup says yes, even if it risks chilling whistleblowers Coming soon: 10 Things That Matter in AI Right Now DARPA built an AI to fact-check enemy weapons claims What explains heterogeneity in AI adoption? When AI Meets Muscle: Context-Aware Electrical Stimulation Promises a New Way to Guide Human Movements - Department of Computer Science AI Changed How We Build. It Did Not Change What Matters. Linux rules on using AI-generated code - Copilot is OK, but humans must take 'full responsibility for the… Meta spins up AI version of Mark Zuckerberg to engage with employees Code Mode: Let Your AI Write Programs, Not Just Call Tools | TanStack Blog GitHub - Delavalom/graft: Go framework for building AI agents. Type-safe tools, multi-provider (OpenAI, Anthropic, Gemini, Bedrock), zero vendor SDKs. India's TCS tops estimates, says new AI models did not dent services demand Gen Z's fading AI hype Strong feeling: we are in a folded AI reality GitHub - machinarii/total-recall-catalog: A reference catalog of latest knowledge retrieval, memory & RAG systems GitHub - mensfeld/code-on-incus: Give each AI agent its own isolated machine with root, Docker, and systemd. Active defense detects and stops threats automatically.. Quantization, LoRA, and the 8% Problem: Benchmarking Local LLMs for Production AI Iran war: We spoke to the man making Lego-style AI videos that experts say are powerful propaganda Powell, Bessent discussed Anthropic's Mythos AI cyber threat with major U.S. banks GitHub - immartian/bellamem: Persistent belief-graph memory for AI agents. Retrieves decisive context by importance — not recency, not RAG, not /compact. recursive-mode: The Repo-Native Operating System for AI Engineering After the attack on Sam Altman's home, will AI CEO's go on the offensive? The biggest advance in AI since the LLM Opus 4.6 vs GPT 5.4 One Prompt Unity World Generation Test “AI polls” are fake polls Client Challenge Can AI be a 'child of God'? Inside Anthropic's meeting with Christian leaders
Can Span turn homes into AI inference hubs?
Catherine Boudreau · 2026-04-13 · via Hacker News - Newest: "AI"

The smart panel company Span will roll out a high-performance edge data center later this year that can be installed in homes and be powered by excess grid capacity, Latitude Media has learned. 

Called the XFRA Node, the mini distributed compute system is paired with Span’s smart panel, which monitors a home’s electricity use in real time, as well as a whole-home battery system. XFRA’s orchestration software can schedule and route artificial intelligence workloads across different nodes based on latency requirements and available energy capacity, the company said. 

“Our hypothesis at Span has been that the existing distribution network operates at only 40 to 45% utilization, nominally,” Arch Rao, founder and CEO of Span, told Latitude Media. “So there’s plenty of headroom on the existing system that can be used in a more effective way. And then we’re able to deliver compute much faster.”

This comes as Span raises its Series C round, with $163 million in equity sold as of February. The company in 2025 expanded its business with a turn toward utilities looking to meet load growth, rather than selling its smart panel to the individual consumer market alone.   

The new compute product will be announced at Latitude Media’s Transition-AI conference this week.  

It arrives as demand for AI computing power outstrips the pace of deploying new power infrastructure in the U.S., due to years-long interconnection queues for new load and generation, equipment shortages, and local opposition. Up to half the data centers worldwide may be delayed this year, according to research by Sightline Climate.

The crunch has created momentum around grid utilization, a broad range of initiatives to unlock capacity via, for instance, shifting large load energy use via demand response, or else building out behind-the-meter resources like battery storage. Distributed computing falls under that grid utilization umbrella: Hyperscalers that buy the resulting compute could avoid the need for expensive new poles and wires — infrastructure that utility customers often end up paying for.

Rao noted that it currently takes between three and five years to build a 100-megawatt data center, and it costs upwards of $15 million per MW. Span can supply the same amount of compute by installing the XFRA Node at 8,000 new homes, which would take roughly six months, he said, at a cost of $3 million per megawatt.

An XFRA pilot is expected to roll out this year in 100 newly constructed homes, or about 1.25 MW of compute capacity across 1,600 direct liquid cooled inference GPUs. Span has several partnerships, including with Pulte Homes, the third-largest homebuilder in the country, which has already been installing Span’s smart panels. 

“They’re able to use Span’s panel technology to stay at 200 amps per home, which reduces the size of interconnection with the utility and the amount of copper in the home,” Rao said. “Now we’re going one step further in our partnership to say, ‘If you also deploy XFRA Nodes in a subset of homes, that has the added benefit of making the home more affordable to their buyers in terms of heavily discounted energy and Internet.’”

Installation is at no cost to homeowners, but they will pay a $150 monthly fee that covers energy and internet, which is a discount on typical monthly costs. Span then sells computing power to customers such as hyperscalers, neocloud companies, and AI companies. Rao said the revenue from selling compute will exceed the cost of the XFRA system itself, and that customers will end up paying less month-to-month. The model is similar to homeowners paying a fixed rate for solar panels on their roofs that are owned by a third party, Rao said — except in this case, Span will own computing assets and backup battery storage.

These small “nodes” can’t replace large, centralized AI data centers, of course, which are needed for training AI models. The nodes are complementary, Rao said, especially for inference, meaning the actual use of AI models such as chatbots, autonomous driving, and medical image diagnostics. As inference becomes the primary source of revenue for AI companies, it will be ideal to locate computing resources closer to users to reduce latency, he added. 

Span is also working on a commercial XFRA Node for early 2027 that can be sited at businesses and office buildings.

  • Catherine Boudreau is a senior reporter at Latitude Media. She’s spent a decade covering, energy, climate and agriculture issues at the intersection of business and policy, at publications including Business Insider and Politico.