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Bryan Catanzaro, NVIDIA’s VP of applied deep learning, told Axios that for his team, “the cost of compute is far beyond the costs of the employees.” He was talking about compute-heavy deep learning work, not every job, but the point is important.

AI does not just cost money once. Every prompt, model run, coding agent, file scan, and generated response can become a recurring compute bill. That is why companies using tools like Claude Code and Cursor at scale are starting to hit budget pressure faster than expected.

Replacing humans with AI sounds simple in theory, but in practice, companies still need GPUs, cloud infrastructure, subscriptions, oversight, and a real return on every token.

Span is partnering with Nvidia and homebuilder PulteGroup to install “mini data centers” on new homes.

They will use Span smart panels, batteries, and Nvidia-powered compute nodes to turn unused household electrical capacity into distributed AI infrastructure. The idea is that instead of waiting years to build massive centralized data centers, AI companies could rent compute from thousands of residential nodes, mainly for inference, while homeowners get discounted energy/internet and backup power.

A 100-home pilot is planned for 2026, with Span arguing this could help ease AI’s power bottleneck by using existing grid capacity more efficiently.

The Pentagon has signed new classified AI agreements with OpenAI, Google, Microsoft, Amazon, Nvidia, xAI, and Reflection, allowing their systems to be used in sensitive Defense Department settings.

Anthropic was left out, despite previously having a $200 million deal for classified work, after the Pentagon labeled it a supply-chain risk amid disputes over the company’s limits on mass surveillance and fully autonomous weapons.

Anthropic has sued the federal government and won a temporary injunction.

The Pentagon says the deals support “lawful operational use” of AI and its push to become an “AI-first fighting force.”

Nvidia’s market value has climbed past the GDP of major countries. The comparison puts Nvidia above Japan, the UK, and India when measured against each country’s nominal GDP.

The driver is AI. Nvidia makes the chips powering the biggest AI systems, and demand for that hardware has turned the company into the center of the AI infrastructure race.

That puts one company in the same financial conversation as entire national economies.

AI is no longer just a software story. It is reshaping where global value is being concentrated.

OpenAI is working with consulting firms like Accenture, Capgemini, and PwC to help sell and roll out its AI coding tool, Codex, to businesses.

This is part of OpenAI’s push to grow in the enterprise market as competition with Anthropic increases.

The company said Codex now has four million weekly users, up from three million just two weeks ago.

These consulting partners will help companies learn how to use Codex and add it into their daily work, including teams like marketing, finance, and sales.

OpenAI is also launching Codex Labs, which will offer hands-on training to help businesses get started faster.

Meta is launching a new workforce initiative aimed at solving a growing bottleneck in the AI boom: skilled labor.

In partnership with CBRE, the company introduced “LevelUp,” a free, four-week training program designed to turn people with no prior experience into fiber technicians—critical workers who build and maintain data center infrastructure.

The program will combine classroom learning with hands-on training, and successful graduates may get job opportunities through Meta’s contractor network.

As demand for AI data centers surges, Meta is investing in talent pipelines to ensure it can scale infrastructure fast enough to keep up with the industry’s rapid growth.

Google signed a classified AI deal with the Pentagon, opening its models to "any lawful government purpose," the same week that 600+ staffers wrote an open letter to CEO Sundar Pichai, calling to reject the use of AI for military purposes.

More than 600 Google employees sent Pichai a letter on Monday asking him to “refuse to make our AI systems available for classified workloads.”

The Information reported that the contract opens Google's AI to “any lawful government purpose”, with no legal right to veto how the Pentagon uses it.

OAI and xAI inked deals with the Pentagon last month, with Anthropic currently fighting in court after being blacklisted for not dropping its guardrails.

Google's no-weapons pledge was scrubbed from its AI principles in 2025, after it was implemented in 2018 following successful staff protests.

The Pentagon drama might still feel fresh in the OAI-vs-Anthropic rivalry, but it’s not discouraging another top AI lab from making a similar deal. Google’s now wading into a messy territory from a PR and internal perspective, and time will tell if the same backlash we saw with ChatGPT now comes to Gemini’s doorstep.

🚨 The U.S. State Department has reportedly warned diplomats worldwide that leading Chinese AI firms including DeepSeek, Moonshot AI, and MiniMax may be using unauthorized model distillation to compete with American labs.

Distillation allows smaller models to learn from the outputs of larger frontier systems, potentially reaching high performance at a fraction of the cost.

That means the future of AI may not only be about who invents first… but who can replicate fastest.

This could become one of the biggest technology conflicts of the decade.

Analyzing websites published between 2022 and 2025, the study estimates that by mid-2025, around 35% of newly created websites contain AI-generated or AI-assisted text.

The researchers also found that this shift is making online content more similar in meaning and noticeably more positive in tone.

However, despite widespread concerns, the study found no strong evidence that AI content is reducing factual accuracy.

The study was conducted by researchers from Imperial College London, Stanford University, and the Internet Archive.

Firefox's latest release patches 271 security vulnerabilities , all identified using Anthropic's Mythos Preview, a new AI model with advanced bug-hunting capabilities. Firefox CTO Bobby Holley says the shift is fundamental: AI can now find categories of bugs that previously required expensive manual analysis, meaning attackers will soon have the same capability. "Every piece of software is going to have to make this transition," Holley warns. The concern is especially acute for open source projects maintained by small teams or volunteers, who may lack the resources to respond at the same speed as larger organizations.