Taking Jaggedness Seriously

Why we should expect AI capabilities to keep being extremely uneven, and why that matters

Open-world evaluations for measuring frontier AI capabilities

Introducing CRUX, a new project for evaluating AI on long, messy tasks

Pacing the Frontier

A statement from over 1000 employees of frontier AI companies

Why it’s getting harder to measure AI performance

The most famous chart in AI might be obsolete soon.

The Jevons Paradox of AI - Wesley's notes

Why AI can make us more productive but will never save us time

How ‘Jagged Intelligence’ Can Reframe the A.I. Debate

A.I. has always been compared to human intelligence, but that may not be the right way to think about it. What it does well can help predict what jobs it may replace.

What we can’t measure about AI – yet | Aeon Essays

The costs of transformative innovations are immediately clear: it’s the longterm gains that are hardest to understand

How does AI impact skill formation?

Two days ago, the Anthropic Fellows program released a paper called How AI Impacts Skill Formation. Like other papers on AI before it, this one is being treated as proof that AI makes you slower and dumber. Does it prove that?

AI FOR EPISTEMICS & COORDINATION

Civilization and technology have radically improved the human condition. Nonetheless, the world sometimes goes in directions which essentially nobody would prefer — e.g., nuclear arms races, unexpected financial crashes, predatory marketing, or ubiquitous political misinformation.

Want to understand the current state of AI? Check out these charts.

According to Stanford’s 2026 AI Index, AI is sprinting, and we’re struggling to keep up.

What AI is Really For - Christopher Butler

After three years of immersion in AI, I have come to a relatively simple conclusion: it’s a useful technology that is very likely overhyped to the

The Bitter Lesson: Rethinking How We Build AI Systems

The Race for AI Progress In 2019, Richard Sutton, wrote his groundbreaking essay titled ‘The Bitter Lesson’. Simply put, the essay concludes that systems which get better with higher compute beat the systems that do not. Or specifically in AI: raw computing power consistently wins over intricate human-designed solutions. I used to believe that clever orchestrations and sophisticated rules were the key to building better AI systems. That was a typical sofware dev mentality. You build a system, look for edgecases, cover them and you are good to go. Boy, was I wrong.

Debates On Frontier Artificial Intelligence Governance: The AI Triad

Analytical Paper Optional: All enrolled students have the option of completing a research paper of at least 20-25 pages, with faculty and peer review of a substantially complete draft. This paper can be used to satisfy the analytical paper requirement for J.D. students. Prerequisite: This course is intended for students intending to work in the […]