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.
The fourth bi-annual Postdocs in Complexity Conference at the Santa Fe Institute provides networking opportunities for early career researchers working on complex systems science, as well as special sessions from SFI faculty and other prominent speakers. This three-day conference will build on the themes of the previous three Postdocs in Complexity meetings, refining the structure to allow additional time to build community and focus on collaborations.
The bane of the language-learner is a goldmine for linguists, cultural evolutionists, and computer scientists, a group of whom will meet at SFI Aug. 27–28, 2018. Given the messy state of linguistic affairs, they ask, is it possible to quantitatively encode “meaning” independent of any particular language?
An SFI Working Group examines the evidence of low-density Maya settlements and the challenge this poses to the idea that density increases with population.
The notion that an attractive person is “out of your league” doesn’t often dissuade dating hopefuls – at least online. In fact, the majority of online daters seek out partners who are more desirable than themselves, suggests a new large-scale analysis published in Science Advances.
In this SFI Community Lecture, science writer Sabine Hossenfelder explains what physicists mean when they say a theory is beautiful, what went wrong with their reliance on it, and how the field can move on. Watch her talk.
A-list for ALIFE: Steen Rasmussen receives Lifetime Achievement Award from International Society for Artificial Life
A small cadre of scientists and entrepreneurs convened a two-week long SFI working group to address the growing gap between our physical and social technologies.
Neuroscientists and complexity scientists meet to develop new tools for studying the brain as a complex network. Their working group, titled “Cognitive Regime Shift: When the Brain Breaks,” is part of SFI’s Aging, Adaptation, and the Arrow of Time research theme, funded by the James S. McDonnell Foundation.
Parakeet pecking orders, basketball match-ups, and the tenure-track: How analyzing winners and losers can reveal rank within networks
In a paper published in Science Advances, researchers from the Santa Fe Institute describe a new algorithm called SpringRank that uses wins and losses to quickly find rankings lurking in large networks. When tested on a wide range of synthetic and real-world datasets, ranging from teams in an NCAA college basketball tournament to the social behavior of animals, SpringRank outperformed other ranking algorithms in predicting outcomes and in efficiency.