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Job post! We are hiring ML Research Scientists at AISI to help explore the technical details of safety cases for advanced AI systems. Please apply if you enjoy mapping out the arguments and open research problems behind a variety of technical safety approaches! 🧵

Obvious caveat: These are MY takes, and I'm sure other researchers disagree on points, or think I'm missing a crucial paper. But I think it's more useful this way. V1 is one of my most popular blog posts, so I hope v2 is useful to people! alignmentforum.org/posts/NfFST5Mi…

Key Republican lawmakers asked the Biden admin to prepare a formal intelligence community assessment of Microsoft’s partnership w Abu Dhabi AI firm G42 Lawmakers say they’ve had “productive” conversations w Microsoft but want more robust natsec guardrails bloomberg.com/news/articles/…

Are you excited about Chris Olah-style mechanistic interpretability research? I'm looking to mentor scholars via MATS - apply by Aug 30! I'm impressed by the work from past scholars, and love mentoring promising talent. You don't need to be in a big lab to do good mech interp work!

in the process of constructing a very daft joke today, i discovered daniel dennett's dad is the first star on the CIA memorial wall

hsm.stackexchange.com/questions/5885…

armen (& Lili Yu (ICLR2025)!) lead one of my fave scaling law papers of recent times, excited to see where this goes arxiv.org/pdf/2301.03728

This is very important to appreciate about the AI risk discourse IMO. I liked this chart from Nate Silver's new book. A lot of people expect AI to top out somewhere between social media and the internet, well short of the rise of Homo sapiens.

A big part of my job these days is to think about what technical work Anthropic needs to do to make things go well with the development of very powerful AI. I digested my thinking on this, plus some of the Anthropic zeitgeist around it, into this piece: sleepinyourhat.github.io/checklist/

🧬What are protein language models (PLMs) actually learning about biology? Our paper introduces InterPLM - a framework that reveals interpretable features in PLMs using sparse autoencoders, giving us a window into how these models represent protein structure and function. 🧵(1/9)

i am subtweeting myself

Anthropic's hosting a social in NYC in mid-June for quants interested in a career jump. Sign up link below! I was a quant trader for 4y, retired 2y, then Anthropic for 4y. Quant trading and retirement were good; Anthropic has been great 🎉 gem.com/form?formID=ed…

i use this chart a bunch in discussions of labor market impacts of AI. it captures two things: * it's one thing to invent a better plough, and another to invent the combustion engine * the success of a paradigm shift comes with a lot of survivorship bias