Two of the most advanced AI labs in the world have independently built models so capable at hacking they won't release them publicly. The IMF is alarmed. So is the Fed. Here's what's actually happening.

Someone firebombed Sam Altman's house. And while we argue about whether to pause, China is not pausing.

There's a moment every parent knows. You hand your kid a credit card for the first time. You've set the limit. You've had the talk. And then you let go. Visa just had that moment with AI agents — and it changes everything about how autonomous commerce works.

Every few centuries, something changes in how human civilization does work. Not the tools. Not the industry. The underlying logic of how capability compounds. We are living inside one of those moments right now.

Milla Jovovich is best known for saving humanity in post-apocalyptic fiction. Last week, she may have done something more useful.

Disney Research, Google DeepMind, and NVIDIA just open-sourced a GPU-accelerated physics simulation engine. It's not just a robotics tool. It's the next proof that math is eating every constraint hardware can't solve.

Jensen Huang said AI needs a system of record to know what's actually true. He was describing enterprise software. But the logical architecture he outlined points somewhere else entirely.

Anthropic cut off 135,000 OpenClaw instances, handed its biggest developer ecosystem to OpenAI, then announced $30B in revenue and a multi-gigawatt compute deal — all in the same week. The pattern has a name.

Google dropped Gemma 4 — four open-source models, Apache 2.0, running locally on consumer hardware, ranking #3 in the world. The open source agent community wired it into OpenClaw within hours. Here's why this changes everything.

TSMC just guided to $52–56 billion in capex for 2026. McKinsey puts the global data center race at $7 trillion. The infrastructure layer is the only play that matters.

AI isn't replacing people. It's replacing unstructured effort. Here's the framework that changes everything — and it starts with one stupid small problem.

Five signals. One conclusion. The grid hit its limit at the very beginning of the demand curve — before 84% of humanity ever typed a prompt. The canary has been dead for a while.

$710 billion committed. Grid queues running 3-5 years. Virginia is full. The bottleneck isn't compute — it's power, and permitted energized land just became a new asset class.

Goldman Sachs, Morgan Stanley, and Jefferies have all stood up dedicated AI infrastructure investment banking practices in the last 90 days. When the banks build teams, the capital follows.

Three people. One room. Fifteen calls. Two meetings playing simultaneously in the same ear. This is what the front lines of the AI infrastructure build-out actually look like.

Oracle fired 30,000 people this morning with a 6 AM email. Not because Oracle is struggling. Because Oracle is winning — and winning now means converting human payroll into AI infrastructure as fast as the balance sheet allows. I want to zoom out from that headline. Oracle is not the story. Oracle is a symptom. The story is what's been building for two years, and what a lot of people are about to finally understand the hard way. I have been saying this since early 2024. The r

This morning, tens of thousands of people woke up, checked their phones, and found out they no longer had a job. Not from their manager. Not from HR. From an email sent by 'Oracle Leadership' at 6:00 a.m. The email was brief, formal, and identical across the US, India, Canada, and Mexico. Your role has been eliminated. Today is your final working day. Sign the DocuSign to receive severance. Your system access has already been revoked. Somewhere between 20,000 and 30,000 peopl

For the last decade, the technology sector has operated under a simple, brute-force paradigm: if you want faster data processing, higher-resolution simulations, or smarter AI, you buy more silicon. You build a bigger data center. You consume more power. But physical infrastructure eventually hits a wall. Today, the constraints of power grids, cooling systems, and memory bandwidth are bottlenecking the next leap in computing. And the industry is rediscovering an old truth: whe

August 2023. That's when I first wrote about it. Not as a prediction. As an observation about something that was already happening — the slow, inevitable collapse of the industrial-era classroom model and the arrival of something better. The piece was called Back to School or a New Dawn in Education? Most people scrolled past it. A few thought I was being optimistic. Some thought I was being naive. This week, Mackenzie Price, co-founder and CEO of Alpha Schools, sat down wit

Everyone thinks Apple lost the AI race. What if they've been playing a different game all along? Not the hyperscaler race. Not the frontier model race. Not even the benchmark race. A different game entirely — the one that matters most when 1.5 billion people carry your hardware in their pocket every single day. Let's talk about what's actually coming at WWDC. And more importantly, what it means for where phones, software, and AI agents are going in the second half of 2026. Fi