In a November SFI Community Lecture, External Professor Michelle Girvan described an exciting new approach to predicting chaotic systems. Watch her talk here.
A study co-authored by SFI Omidyar Fellow Jacopo Grilli sheds new light on a long-standing question about what triggers cell division.
This November 5-7, a working group brings early-career scientists together at SFI to imagine a collective vision for the future of ecological networks.
Introduction to the Theory of Complex Systems synthesizes hundreds of disparate findings in complexity and articulates a single, underlying characteristic of complex systems.
R&D Magazine has selected former SFI External Professor Bette Korber to receive their prestigious Scientist of the Year Award for 2018, recognizing her innovative approach to developing an HIV vaccine.
An SFI working group explores the parallels between ancient and modern societies’ challenges in managing risk and what lessons might be found there.
Identifying meaningful information is a key challenge to disciplines from biology to artificial intelligence. In a new paper, SFI's Artemy Kolchinsky and David Wolpert propose a broadly applicable, fully formal definition for this kind of semantic information.
Sending instantaneous messages across long distances, or quickly computing over ungodly amounts of data are just two possibilities that arise if we can design computers to exploit quantum uncertainty, entanglement, and measurement. In this SFI Community Lecture, scientist Christopher Monroe describes the architecture of a quantum computer based on individual atoms, suspended and isolated with electric fields, and individually addressed with laser beams.
October 13-16, graduate students can meet with leading scientists to learn about modeling and evaluating the future of human populations and their environments. Free tuition for accepted students. Apply before July 11, 2018.
A group of ecologists, cultural anthropologists, geoscientists, and archaeologists studying the unique and myriad ways that humans interact with other species across space and time meets for the third time at SFI.
An SFI workshop examines the key impediments to building machines that understand meaning, and how much understanding is necessary for artificially intelligent machines to approach human-level abilities in language, perception, and reasoning.
The autumn Applied Complexity Network meeting “Risk: Retrospective Lessons and Prospective Strategies,” explores what we have learned since the financial crisis of 2008.
In a two-part lecture series September 24 and 25, SFI Professor Cristopher Moore looked at two sides of computation — the mathematical structures that make problems easy or hard, and the growing debate about fairness in algorithmic predictions. The videos are now available.