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.
A new study suggests that defenses against extreme temperatures give E. coli bacteria an advantage in fending off certain drugs.
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.