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Maria Popova

@mariapopova.bsky.social

Tired of letting algorithms divine who you are, define what you see, and distract you with ads? Try the Marginalian newsletter—an oasis of undistracted inspiration and illumination, free, ad-free, algorithm-free, fully human since 2006: themarginalian.org/newsletter

October 1, 2025 at 7:04 PM

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Santa Fe Institute

@sfiscience.bsky.social

SFI President David Krakauer joins The Generalist Podcast to talk about intelligence, the influence of AI on human thinking, and how to preserve creativity and understanding in a rapidly changing information landscape.

Watch the full interview: www.youtube.com/watch?v=SSBL...

Maintaining Human Intelligence in the AI Era | David Krakauer (President of the Santa Fe Institute)

YouTube video by The Generalist

www.youtube.com

September 23, 2025 at 5:12 PM

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Maria Popova

@mariapopova.bsky.social

The courage to be yourself – Virginia Woolf on how to hear your soul www.themarginalian.org/2023/09/12/v...

The Courage to Be Yourself: Virginia Woolf on How to Hear Your Soul

“Beyond the difficulty of communicating oneself, there is the supreme difficulty of being oneself.”

www.themarginalian.org

September 15, 2025 at 3:28 PM

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Nicole Rust

@nicolecrust.bsky.social

It's publication day for 📘Elusive Cures. What a moment! 1st book, 1st time on Mindscape (which, as many of you know, is one of my favorite podcasts).

Here, @seanmcarroll.bsky.social and I have a wide-ranging conversation around: Why are brain and mental disorders so hard to understand and treat?

Sean Carroll @seanmcarroll.bsky.social · Jun 9

Mindscape 317 | Nicole Rust @nicolecrust.bsky.social on Why Neuroscience Hasn't Solved Brain Disorders. Or, why Bench to Bedside is harder than it sounds. #MindscapePocast

www.preposterousuniverse.com/podcast/2025...

Title card for podcast episode with Nicole Rust.

June 10, 2025 at 11:33 AM

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Benjamin Rosenbaum

@benrosenbaum.bsky.social

I completely re-worked my course "Introduction to Bayesian statistics with brms" and taught it for the 1st time this week. It is meant as a tutorial for ecologists, but should be general enough for other sciences as well
github.com/benjamin-ros...
#stats #Rstats #brms #Stan #Bayesian

GitHub - benjamin-rosenbaum/bayesian-intro: Introduction to Bayesian statistics

Introduction to Bayesian statistics. Contribute to benjamin-rosenbaum/bayesian-intro development by creating an account on GitHub.

github.com

February 28, 2025 at 9:19 AM

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Richard McElreath 🐈‍⬛

@rmcelreath.bsky.social

Part 2 is out! Continue with the epic story of how basic trigonometry (and very precise measurement) establishes the scale of the cosmos. This is much more soothing than whatever else you are scrolling. www.youtube.com/watch?v=hFMa...

February 24, 2025 at 11:45 AM

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Sean Carroll

@seanmcarroll.bsky.social

Mindscape 306 | Helen Czerski @helenczerski.bsky.social on Our Energetic Oceans. #MindscapePodcast

www.preposterousuniverse.com/podcast/2025...

Title card for Mindscape episode with Helen Czerski.

February 24, 2025 at 1:59 PM

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Sean Carroll

@seanmcarroll.bsky.social

Mindscape Ask Me Anything, February 2025. Mercifully short on politics, except for me in the intro putting things in perspective for listeners from the future. And a few moments of existential anxiety along the way. #MindscapePodcast

www.preposterousuniverse.com/podcast/2025...

Title card for AMA episode of Mindscape.

February 3, 2025 at 1:08 PM

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Richard McElreath 🐈‍⬛

@rmcelreath.bsky.social

In honor of Lynch, this scene right here from Twin Peaks is a good summary of my teaching philosophy www.youtube.com/watch?v=kf0Z...

Albert's path

YouTube video by lordofflies

www.youtube.com

January 17, 2025 at 5:59 AM

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Richard McElreath 🐈‍⬛

@rmcelreath.bsky.social

These popular articles face the problem of trying to explain maximum entropy using metaphors instead of mathematics. Not sure what simple, cartoon example could work for maxent? My book has half a chapter on it, but not sure many people read that chapter! But I loved writing it.

Figure10.1. Entropyasameasureofthenumberofuniquearrangements of a system that produce the same distribution. Plots A through E show the numbers of unique ways to arrange 10 pebbles into each of 5 different dis- tributions. Bottom-right: The entropy of each distribution plotted against the log number of ways per pebble to produce it.

Overthinking: The Wallis derivation. Intuitively, we can justify maximum entropy just based upon the definition of information entropy. But there’s another derivation, attributed to Graham Wallis,162 that doesn’t invoke “information” at all. Here’s a short version of the argument. Suppose there are M observable events, and we wish to assign a plausibility to each. We know some constraints about the process that produces these events, such as its expected value or variance. Now imagine setting up M buckets and tossing a large number N of individual stones into them at random, in such a way that each stone is equally likely to land in any of the M buckets. After all the stones have landed, we count up the number of stones in each bucket i and use these counts ni to construct a candidate probability distributiondefinedbypi =ni/N.Ifthiscandidatedistributionisconsistentwithourconstraints,we add it to a list. If not, we empty the buckets and try again. After many rounds of this, the distribution that has occurred the most times is the fairest—in the sense that no bias was involved in tossing the stones into buckets—that still obeys the constraints that we imposed.

$If we could employ the population of a large country in tossing stones every day for years on end, we could do this empirically. Luckily, the procedure can be studied mathematically. The probabil- ity of any particular candidate distribution is just its multinomial probability, the probability of the observed stone counts under uniform chances of landing in each bucket: N!YM1ni N!1N 1N Pr(n1, n2, ..., nm) = n1!n2!...nm! i=1 M = n1!n2!...nm! M = W M The distribution that is realized most often will have the largest value of that ugly fraction W with the factorials in it. Call W the multiplicity, because it states the number of different ways a particular set of counts could be realized. For example, landing all stones in the first bucket can happen only one way, by getting all the stones into that bucket and none in any of the other buckets. But there are many more ways to evenly distribute the stones in the buckets, because order does not matter. We care about this multiplicity, because we are seeking the distribution that would happen most often. So by selecting the distribution that maximizes this multiplicity, we can accomplish that goal. We’re almost at entropy. It’s easier to work with N1 log(W), which will be maximized by the same distribution as W. Also note that ni = Npi. These changes give us: 11�X N log W = N log N! − 11XX log[(Npi)!] Now since N is very large, we can approximate log N! with Stirling’s approximation, N log N − N: log W ≈ N log N − N − (Npi log(Npi) − Npi) = − pi log pi NNii And that’s the exact same formula as Shannon’s information entropy. Among distributions that satisfy our constraints, the distribution that maximizes the expression above is the distribution that spreads out probability as evenly as possible, while still obeying the constraints. This result generalizes easily to the case in which there is not an equal chance of each stone landing in each bucket.163 If we have prior information specified as a probability qi that …$

December 22, 2024 at 8:04 AM

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David Ullrich

@davidullrich202.bsky.social

Decline of Reflective Low Clouds May Have Contributed to Recent Record Heat

A new study links decreasing cloud cover to last year’s spiking heat, adding to research showing Earth’s loss of luster is increasing warming.

insideclimatenews.org/news/0512202...

docs.google.com/document/d/1...

Decline of Reflective Low Clouds May Have Contributed to Recent Record Heat - Inside Climate News

A new study links decreasing cloud cover over the ocean to last year’s spiking heat, adding to research showing Earth’s loss of luster is increasing warming.

insideclimatenews.org

December 14, 2024 at 8:22 AM

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Robbi Bishop-Taylor 🛰️🌏

@satellitesci.bsky.social

One of my favourite data discoveries this year: Google's mind-blowing ARCO-ERA5 dataset: hourly data for ~300 climate variables, available globally from 1940! 🤯

Loadable with a single line of Python code from a single cloud-friendly Zarr file! Below: a month of wind waves + swell: 🌊

November 27, 2024 at 4:02 AM

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Melanie Mitchell

@melaniemitchell.bsky.social

Episode 5 of our podcast is out! We discuss how complicated it is to assess intelligence, whether in humans, animals, or machines.

With two fantastic guests: Comparative Psychologist Erica Cartmill and Computer Scientist Ellie Pavlick.

Check it out!

complexity.simplecast.com/episodes/nat...

Nature of Intelligence, Ep. 5: How do we assess intelligence? | COMPLEXITY

When it comes to assessing intelligence, people have all kinds of tests — the SAT, IQ tests, and so on. There’s controversy over how fairly these tests really measure human intelligence, but at the ve...

complexity.simplecast.com

November 20, 2024 at 9:01 PM

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Melanie Mitchell

@melaniemitchell.bsky.social

First episode of our new podcast is out!

Episode 1: "What is Intelligence?"

It's hard to fully answer this question, but we had some great discussions about it with superstars Alison Gopnik and John Krakauer.

Give it a listen!

complexity.simplecast.com/episodes/nat...

complexity.simplecast.com

September 25, 2024 at 8:51 PM

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Stephen Wild

@stephenjwild.bsky.social

Created a starter pack of Bayesians. It is *very* biased by who I engage with regularly and who I know is on this site. Let me know if you want to be added to the list or know someone who should be.

#stats

go.bsky.app/UfgChHe

September 1, 2024 at 3:07 PM

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J. Doyne Farmer

@doynefarmer.bsky.social

The publication date for my new book is getting closer! Making Sense of Chaos: A Better Economics for a Better World is out on 25 April.

Making Sense of Chaos

We live in an age of increasing complexity, where accelerating technology and global interconnection hold more promise – and more peril – than any other time in human history. The fossil f...

www.penguin.co.uk

February 14, 2024 at 2:18 PM

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INET Complexity Economics

@inet-complexity.bsky.social

Interested in how #ComplexityEconomics is revolutionising our ability to predict the economy, with new approaches to global problems like climate change, inequality, and the impact of financial crises? You'll be excited to know that @doynefarmer.bsky.social's new book is out on 25 April!

Making Sense of Chaos: A Better Economics for a Better World

A preview of J.Doyne Farmer's upcoming book

www.inet.ox.ac.uk

February 14, 2024 at 2:26 PM

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Santa Fe Institute

@sfiscience.bsky.social

🌐 New New Yorker article by SFI's Dan Rockmore explores the power & pitfalls of #MathematicalModels in neurosurgery, climate science, election forecasting, and more!

⚠️ Discussing model evolution & warning against over reliance w/o understanding.

🔗 www.newyorker.com/culture/anna...

January 16, 2024 at 6:27 PM

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Sean Carroll

@seanmcarroll.bsky.social

Mindscape 242 | David Krakauer on Complexity, Agency, and Information. #MindscapePodcast
https://www.preposterousuniverse.com/podcast/2023/07/10/242-david-krakauer-on-complexity-agency-and-information/

242 | David Krakauer on Complexity, Agency, and Information – Sean Carroll

www.preposterousuniverse.com

July 10, 2023 at 1:34 PM

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Posit

@posit.co

The 2023 Posit conference had fantastic content for those interested in #RStats and #Python data modeling and analysis.

@topepo.bsky.social put together a useful list of modeling-related talks and workshops in our latest blog post!
posit.co/blog/modelin...

Modeling at posit::conf(2023): Talks and Workshops - Posit

posit.co

January 3, 2024 at 4:17 PM

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Lynda Albertson

@sauterne.bsky.social

Despite frequent remonstrations, Persephone never accepted that she could not photocopy a whole book in one go.

December 6, 2023 at 7:02 PM

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Michael Boo-tancourt

@betanalpha.bsky.social

The structure of this course, shiraamitchell.github.io/nmaist_stati... , by Shira Mitchell and colleagues is fantastic..

In order to better integrate science into statistics and vice versa we need more teaching like this and fewer exercises that just run black box methods on black box data.

STATISTICAL WORKFLOW:

shiraamitchell.github.io

November 25, 2023 at 8:36 PM

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Richard McElreath 🐈‍⬛

@rmcelreath.bsky.social

I told a colleague that logistic regression is AI and they got mad at me, so I made a chart. Find yourself. I am "Tinder is AI". (I posted this on that other site and a friend complained "y u no skeet this too!?!!?" so here you go)

Table with 3 rows and 3 columns.
Rows: (1) Algorithm purist (mimic human cognition), (2) Algorithm netural (learns & generalizes), (3) Algorithm rebel (method irrelevant)
Cols: (1) Ability purist (exceeds human ability), (2) Ability neutral (makes task easier), (3) Ability rebel (usefullness questionable)
Cells:
[1,1] "Terminator is AI" [1,2] "C3PO is AI" [1,3] "WALL-E is AI"
[2,1] "AlphaGo is AI" [2,2] "XGBOOST is AI" [2,3] "Tinder is AI"
[3,1] "A metal detector is AI" [3,2] "Bubble sort is AI" [3,3] "Magic 8 Ball is AI"

August 25, 2023 at 8:21 AM

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Richard McElreath 🐈‍⬛

@rmcelreath.bsky.social

Yes I will offer my online science-focused Statistical Rethinking course again starting in January 2024. Registration going up at the end of this month. All the course materials are already online though, so why wait? Update your posterior starting today 🧪 #stats www.youtube.com/watch?v=FdnM...