Asst Prof @UCMerced, formerly @SFIscience | cognition, complexity, culture, communication moved to 🟦🌞: https://nitter.cf/t.co/LC48POJ3wq
Merced, California. he/him
Joined June 2015
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Tyler Marghetis retweeted
What is mathematics, how do we do it, and how will A.I. change it for ever?
Thrilled to announce Explaining Universal Truths, a @templeton_fdn & @CMU_DietrichHSS project to fund an interdisciplinary team of philosophers, mathematicians, and cognitive scientists. We're hiring!🧵
Tyler Marghetis retweeted
The cool thing is that our approach isn’t limited to math. All you need is a time series of discrete events. We’re excited to look at creative breakthroughs in artists, scientists, writers... Got data? Let’s collaborate! (8/n)
Tyler Marghetis retweeted
🚨 Hot off the press! 🚨
Eureka moments feel like ⚡️lightning⚡️— sudden, brilliant, impossible to predict. Gauss thought of them as “divine intervention.” But in our new @PNASNews paper, we show that you can actually tell when a breakthrough is coming… 🧵(1/n)
Tyler Marghetis retweeted
PNAS
An information-theoretic foreshadowing of mathematicians’ sudden insights
pnas.org/doi/10.1073/pnas.25…
Tyler Marghetis retweeted
Researchers filmed 6 mathematicians at the blackboard. Just before their “aha!” moments, their writing and gestures grew more erratic—suggesting that insights may have detectable "early warning signs" in behavior. pnas.org/doi/full/10.1073/pn…
Tyler Marghetis retweeted
Video taping mathematicians having IMO-level insights! An absolutely delightful paper by Shadab Tabatabaeian, @TylerMarghetis and a team at @UCMCogSci on mathematical creativity and ah-ha moments. pnas.org/doi/10.1073/pnas.25…
🚨 Hot off the press! 🚨
Eureka moments feel like ⚡️lightning⚡️— sudden, brilliant, impossible to predict. Gauss thought of them as “divine intervention.” But in our new @PNASNews paper, we show that you can actually tell when a breakthrough is coming… 🧵(1/n)
The cool thing is that our approach isn’t limited to math. All you need is a time series of discrete events. We’re excited to look at creative breakthroughs in artists, scientists, writers... Got data? Let’s collaborate! (8/n)
A hearty congrats-slash-thanks to 1st author Shadi Tabatabaeian, who led this project during her PhD @ucmerced, and the rest of the team: Arta O’bi & David Landy. I really love this paper. I’m happy it’s out in the world. (9/9, FIN)
Full paper 👉 pnas.org/doi/10.1073/pnas.25…
Tyler Marghetis retweeted
How do we enter and exit moments of deep engagement? How do multiple episodes of flow-like deep engagement weave into the joys and pains, downs and ups of skill mastery? A formula for a life of learning? nature.com/articles/s44260-0… @VickyCYang @TylerMarghetis
Tyler Marghetis retweeted
Mastering a skill can take decades, but the learning process unfolds across multiple timescales, from mere moments to days. A new paper by three former SFI postdoctoral fellows presents a theoretical model of nested timescales of learning, offering a unified, multi-scale account of skill acquisition.
The study grew from a conversation between co-authors @mingzhen_lu, @VickyCYang, and @TylerMarghetis during SFI's 2020 Postdocs in Complexity conference.
santafe.edu/news-center/news…
ALT Ceramicist at work in Takayama, Japan. (image: Katherine Mast)
Tyler Marghetis retweeted
🚨Big personal and professional news! I'll be giving talks at UC Berkeley and Stanford this week about "The Financialized University Under Threat" and my new newsletter.
Please subscribe here for more: charlieeaton.net
Tyler Marghetis retweeted
Here’s the key figure: people make the same estimation errors regardless of what they are estimating---political and *entirely non-political* quantities.
These are 100k estimates of the size of racial and non-racial groups made by 37k people in 22 countries
Tyler Marghetis retweeted
🚨Out today in PNAS @PNASNews🚨
pnas.org/doi/10.1073/pnas.24…
Why do people overestimate the size of politically relevant groups (immigrant, LGBTQ, Jewish) and quantities (% of budget spent on foreign aid, % of refugees that are criminals)?
We analyze 100k estimates to find out🧵👇
