1/ With @BenDLaufer and Jon Kleinberg, we constructed the largest dataset of its kind to date: 1.86M Hugging Face models. In a new paper, we mapped how the open-source AI ecosystem evolves by tracing fine-tunes, merges, and more. Here's what we found 🧵

Yeah this type motion!!!

🚨 We're open-sourcing Druids, a library for coordinating and deploying coding agents across machines. Our beta users have used Druids to work on open math problems, conduct ML "autoresearch," and make software faster.

Ima have the champion project of the summer I don't think algorithms gone stop the soul from playing a music that charges you up and not turn you down in the good or bad times of life!!

Wrote a new essay with @AbramovichShira for @reboot_hq on procedural data extraction, consumer platforms, what it means for privacy, and the parallels to the attention economy! Cover art is a h/t to Daniel Dennett's "Cartesian theater" by @connie_surf :)

Interact is a fellowship for 19-23 year old technologists, or rather smart people interested in thinking about or working on technology. The community has changed my life and the life of many of my friends for the better. Applications are open now til Feb 9th :) joininteract.com/

How could tiny breakthroughs in aging science change U.S. GDP and population growth? What’s the economic value of making 41 the new 40, or 65 the new 60? How many lives could we create or save if we could slow reproductive or brain aging by just 1 year? What would billions of healthier hours be worth to the economy, if we assume no change in the age of retirement? I spent the last two years obsessing over the design, research, and execution of this project. The result is a book upcoming with Harvard University Press, a preprint, and—maybe your favorite part—an interactive simulation tool that lets you input your own timelines and assumptions for specific breakthroughs in aging bio, then see the ROI in terms of US population & GDP growth. From @RickEcon and Jason DeBacker—the economists who co-developed the open-source, macro model that made this project possible—to extensive comments by @tylercowen, @sapinker, Richard Freeman, @NDHendrix, @ebudish, @elidourado, @geochurch, @jasoncrawford as well as interviews with 102 scientists (!) and countless iterations with award-winning designer Giorgia Lupi and the @pentagram team, we built something we hope will be a benchmark for how scientists, economists, designers, philosophers, entrepreneurs and storytellers can come together to paint, fund, and build different flourishing futures for our species. I couldn’t be more excited to share this. It’s the start of an open and evolving project—the labor and product of love, obsession, and unrelenting care. I hope you have fun playing with our simulation tool — and if you do, please share!

Introducing Splat 🟨📌: Affinity diagramming in a single HTML file. Drag notes and organize ideas on a visual board. With semantic search and an agentic AI assistant. Open source and fully local. (🧵1/6)

We’ll be presenting this paper at the NeurIPS RegML workshop! Looking forward to meeting people in town this week

I built papiers.ai, a new interface for arXiv As we enter an era of accelerated scientific discovery, we need better tools that augment human cognition to help us keep up. Try it: visit papiers ai or swap arxiv -> papiers on any paper URL

How can we incentivize AI for national priorities? @sebkrier and @zhengdongwang explain how commissioning the creation of benchmarks and evaluations can steer AI development toward important outcomes that will otherwise be neglected. Benchmarks can have a large impact: When benchmarks make AI progress legible, progress can accelerate dramatically. After FrontierMath launched in 2024, AI scores jumped from 2% to 25% in just months. It's not crazy to think that AI progress in math would've been slower without a high-quality target. AlphaFold solved protein folding a decade ahead of schedule by targeting the CASP benchmark. Imagine that speed applied to clinical trials or clean energy. Benchmarks are high-leverage, low-cost ways of steering AI development: Frontier AI training costs billions, but influential benchmarks can be launched by small, committed teams for a fraction of that. Humanity's Last Exam mobilized 1,000 global contributors with just $500K. The US government can set the target, and let others reach the solution. Here's the online piece, if you can't wait for the book: ifp.org/benchmarking-for-bre…

New paper: A Research Agenda for the Economics of AI Training Data We explore: - Why data is hard to price (nonrival, heterogeneous) - How markets evolved for previous assets - Recent AI training data deals - Data as distinct from labor or capital in the production function

1/ OPT OBSERVATORY I’ve spent the past year creating *the most in-depth public resource* on how the US retains international students after they graduate. Today, @IFP is releasing never-before-seen data we obtained from ICE via FOIA. Check it out: optobservatory.org

The first self-serve platform for user-owned data! Vana Playground is live. Explore structured datasets before running privacy-preserving jobs, accessing data that's usually locked behind walled gardens

Thank you to @cosmos_inst and @TheFIREorg for their support! Looking forward to working on research tooling and more in the months ahead, started at @southpkcommons :)