UlrikeHahn, to Neuroscience German
@UlrikeHahn@fediscience.org avatar

Thought I‘d try something: this book by Juerrero has come up a lot in some of the most interesting conversations I‘ve had on this platform about , and and systems but it‘s not an easy read. I am now determined to tackle it and will be posting updates as I go…

care to join me? OA at https://mitpress.mit.edu/9780262545662/context-changes-everything/

itnewsbot, to philosophy
@itnewsbot@schleuss.online avatar

The DeDeterminator Uses Quantum Physics To Make Decisions So You Don’t Have To - Are you making your own decisions and mainlining causality like a sucker? Why go t... - https://hackaday.com/2024/02/26/the-dedeterminator-uses-quantum-physics-to-make-decisions-so-you-dont-have-to/

nurkiewicz, to random
@nurkiewicz@fosstodon.org avatar

Recent research shows that the major cause of car accidents with kangaroos is caused by left-hand traffic in Australia. Such accidents don't happen in countries with right-hand traffic. vs

br00t4c, to random
@br00t4c@mastodon.social avatar

The problems started with my resolution next year to reject temporal causality.

https://imgs.xkcd.com/comics/empiricism.png

br00t4c, to random
@br00t4c@mastodon.social avatar
mjambon, to politics
@mjambon@qoto.org avatar
jimdonegan, to physics
@jimdonegan@mastodon.scot avatar
nixCraft, to random
@nixCraft@mastodon.social avatar
rameshgupta,
@rameshgupta@mastodon.social avatar

@nixCraft

Everything changed when became president

Neurograce, to Neuroscience

What are the foundational principles of ? By which I mean: beliefs or assumptions that animate our study of the brain across topics. Things like a belief in a structure-function relationship or the neuron as the base unit.

teixi,
@teixi@mastodon.social avatar

@manisha @Neurograce @neuroscience @cogsci @cogneurophys @PessoaBrain

@cian comment in thread reminded me:

@kordinglab recent talks on how methods, while spread across labs & papers, still face proven grounds:

Does the do ?
https://www.youtube.com/watch?v=E5hATeCZQnU

for & beyond
https://www.youtube.com/watch?v=XUD69JshQTk



ps: IMHO yea: best when for discovery, not causality

gerald_leppert, to random

Why artificial intelligence needs to understand consequences (www.nature.com)

This is the potential development in AI I'm most interested in. So naturally, I tested this when I first used ChatGPT. In classic ChatGPT fashion, when asked to make a directed acyclic graph representing cause and effect, it could interpret that well enough to make a simple graph...but got the cause and effect flow for something...

medigoth, to random
@medigoth@qoto.org avatar

With the usual ’s caveat that is really hard to sort out in data like this even with good … yes, I believe this. And the aren’t hard to find, either. 😐

peter_ellis, to random

I had fun simulating confounder, collider and mediator variables with to re-create a great diagram by Wysocki et al that helps understand and regression modelling strategy: http://freerangestats.info/blog/2023/06/04/causality-sims

bronger, to random
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