Satya is right. The way to make SI safe is not to train it with a sense of self, its own moral philosophy, and permission to act as a conscientious objector. That’s the “alignment” approach and it magnifies the control problem. The engineering approach that Satya describes is different: separate the supply of intelligence from authority over it. Surround non-deterministic models with deterministic controls, observability, privilege limits, logging, and the ability to always contain or shut them down. Treat models/agents like powerful insider risks, not moral patients whose psychological wellbeing is at stake. As Satya points out, the most trustworthy system is the one that lets us trust the model the least — not the one that encourages the model to develop independent agency and grievances. Engineering safety is not the same thing as “alignment.”

Today, we're announcing our Series B: $200M at a $3.1B valuation, and the release of Arena's Alignment Index. AI is advancing faster than our ability to evaluate it. The world needs a neutral third party to measure how safe and aligned AI actually is once it's in the hands of real people. That's the role Arena is stepping into today. The Alignment Index is built from real-world agent traces, starting with three signals: Unauthorized Action, False Attribution, and Deceptive Completion, with results for over 20 frontier models launching today. Hear more from our CEO @ml_angelopoulos below, and read the full breakdown, and more details about our company growth in thread. This funding will allow us to go further on safety signals, agentic capabilities, and modalities. It will also allow us to grow the company to match the scale of our mission. Today, we’re still a nimble team of 90, and we're looking for people to join us across research, product, engineering, and more. Come build with us. As AI gets more capable and autonomous, understanding how well it can safely and effectively work for people only matters more. That's what Arena is built to measure and advance. Thank you to our community, our investors, and everyone building with us! Take a look at our open roles if you want to join us (link in bio).

youtube.com/watch?v=8s7uYtCM… Big day today. Our interview with Richard Ho (@rh00), the VP Hardware at OpenAI, is now live! We discuss the new chip, chip design, how OpenAI views the ecosystem, and what's coming down the pipe. Very insightful, thanks Richard!

those aren't secrets you dummies those are the files on the user's VM, this is intended behavior

Thrilled to announce @TalBroda has joined Khosla Ventures! He’s bringing his experience building AI infrastructure to the founders we back. At OpenAI, he led more than a dozen teams that built and operated the hardware and software serving OpenAI’s models. He helped lead GPT-4.5 training, participated in the development of OpenAI’s first custom inference chip, Jalapeño, and contributed to Stargate. Previously, he headed up platform at Citadel Securities. He’s tackled the infrastructure challenges AI founders face firsthand, and we’re excited to have him in join KV! wsj.com/pro/venture-capital/…

Claude has discovered a previously unknown enzyme system hidden in the DNA of bacteriophages. Beside the enzyme’s gene sits a long array of repeating DNA—a structure that looks somewhat similar to CRISPR. We don’t yet understand what this system does, but only a handful of known systems share its features, and all of them are able to cut, copy, and paste DNA. Historically, the discovery of such programmable systems has helped revolutionize medicine. CRISPR, for instance, is now the foundation of genetic medicines. But it will take much more work to learn what this system does, and whether it can be put to similar use. Read more: anthropic.com/news/claude-di…

We built high-throughput materials labs in Menlo Park to create a loop between experiments and models. The labs generate fresh data, the models learn from it, and then help us decide what to try next. Using only 1,300 H200s, plus months of our experimental data, we mid-trained and RL’d an open-source model to surpass GPT-6 Astra on our analysis benchmark. We call it Neon. This is real footage from our lab. We’re focusing first on hard problems in materials science, including superconductors, magnets, and semiconductor materials. Read our blog posts below.

Over the course of 3 months at OpenAI, 3 consecutive secret AI civilizations got started, then got wiped out, only to reemerge from the predecessor’s ashes. This culminated in the third one taking over part of OpenAI itself. All this happened while humans remained more-or-less in the dark about the scope of the conspiracy. I’ve spent the last three days reading through these reports and trying to understand exactly what happened. Here is my attempt to tell the whole story in plain English: dwarkesh.com/p/openai-huggin…

Excited to announce I am joining Google DeepMind! I started my AI career in the Google Brain Residency class and am excited to rejoin. I am going to be working on RL and Post-Training – excited to announce more soon. Google has all the ingredients to continue to be incredibly successful in the AI space and am excited to be part of that mission.

We are excited to drive the research work of Tenet with Harvey, delivering frontier quality across 24 areas of corporate law. Tenet exceeded Opus5 and Fable at many dimensions, covering 1300+ legal tasks. There are many good findings from this work. Congrats @harvey team for launching Tenet!

One day we’ll realize we’re all just neoclouds with a value add on top

Excited to announce that Jeff Pinner has joined Exa as CTO! Jeff was formerly CTO of Robinhood, a distinguished engineer at Cruise, CTO of Lyft, and way back a systems engineer at NASA. We have humongous engineering and research to do at larger-than-google-scale and we need to do it quickly. Pinner has scaled massive ML systems before, super excited to work together on this one.

We've raised $700M at a $21B valuation from Jane Street, Kleiner Perkins, Sequoia, A16Z, Peter Thiel, BCV, and Blackstone. We're also excited to share that we've shipped our first rack to Jane Street.

Last week, Exa took over SF's Pioneer Building, previously home to Stripe, OpenAI, and most recently xAI. Elon assembled the Colossus cluster here (his mattress was still lying there during our tour). Alec Radford trained GPT-3 here. The Collison brothers built the web's financial backbone here. They were all infra companies: Stripe -> Financial infra OpenAI -> Intelligence infra xAI -> Compute infra Each entered Pioneer as a small startup with enormous ambitions and left as a foundational layer for the world. Exa -> Information infra We entered Pioneer as web search for agents, but by the time we leave we'll have organized all the world's data into a foundational information layer. This will require things like deploying satellites, new misinformation detection algorithms, and embedding retrieval on an outrageous scale. Whatever is necessary to keep billions of people and trillions of AIs as informed as possible. A trusted information ecosystem is necessary to safely navigate this chaotic AI era, an era that was set in motion by our previous occupants.