Matthew Salganik

@msalganik.bsky.social

Professor of Sociology, Princeton, www.princeton.edu/~mjs3 Author of Bit by Bit: Social Research in the Digital Age, bitbybitbook.com

This is a wonderful story pulling together our research on predicting life trajectories. Thank you @anilananth.bsky.social

Princeton Laboratory for Artificial Intelligence@princetonainews.bsky.social · 6mo ago

New Deep Dive from @anilananth.bsky.social on our blog: @msalganik.bsky.social & colleagues developed a way to create and analyze an individual’s "Book of Life." The eventual goal? Train language models on data from millions of Books of Life to predict an individual's life outcome: bit.ly/473NmIy

New Deep Dive from @anilananth.bsky.social on our blog: @msalganik.bsky.social & colleagues developed a way to create and analyze an individual’s "Book of Life." The eventual goal? Train language models on data from millions of Books of Life to predict an individual's life outcome: bit.ly/473NmIy

The Book of Life: Moving from a Sociology of Variables to a Sociology of Events – Princeton Laboratory for Artificial Intelligence Research Blog

bit.ly

Happy to share the results and open-source code for our benchmark test of GPUs in secure computing environment. Thank you to our wonderful colleagues at ‪@esciencecenter.bsky.social‬. Code is open-sourced for others to use and improve. No private data required.

Netherlands eScience Center@esciencecenter.bsky.social · last yr.

In the latest blog, we learn how the open-source benchmark compares training speed across different supercomputers, including secure environments. Key takeaways? Hardware differences drive performance gaps and multi-GPU scaling is efficient. Learn more: