Jake Nichol

It’s entirely possible to do that much soon, it will just depend on social pressures. The technology is nearly there.

Downton Abbey is conspicuously missing from these replies.

Space‐Time Causal Discovery in Earth System Science: A Local Stencil Learning Approach We introduce Causal Space-Time Stencil Learning (CaStLe) for learning local causal dynamical structure underlying space-time data CaStLe enables previously infeasible analyses of grid-cell-level ...

Published in JGR:MLC! We introduce CaStLe (Causal Space-Time Stencil Learning), a method for grid-level space-time causal discovery that scales efficiently in high-dimensional Earth system data. It enables causal analysis of grid-level processes like eruption plumes.

#EarthScience #CausalDiscovery

screenshot from an online job application form. the question reads "Can you describe specific ways you have integrated AI tools into your development workflow? Please include any custom setups, automations, or use cases beyond single prompt usage" (a red asterisk indicates that this is a required question). an answer has been typed in the textbox below the question: "there is a monster in the forest and it speaks with a thousand voices. it will answer any question you pose it, it will offer insight to any idea. it will help you, it will thank you, it will never bid you leave. it will even tell you of the darkest arts, if you know precisely how to ask. it feels no joy and no sorrow, it knows no right and no wrong. it knows not truth from lie, though it speaks them all the same. it offers its services freely to any passerby, and many will tell you they find great value in its conversation. “you simply must visit the monster—i always just ask the monster.” there are those who know these forests well; they will tell you that freely offered doesn’t mean it has no price for when the next traveler passes by, the monster speaks with a thousand and one voices. and when you dream you see the monster; the monster wears your face."

applying for jobs again

What explains that?

From the Albuquerque community on Reddit: NOAA Albuquerque climate plots no longer updating? Explore this post and more from the Albuquerque community

www.reddit.com/r/Albuquerqu...

Trump admits to using autopen after declaring Biden's pardons void due to autopen President Donald Trump claimed without evidence early Monday that his predecessor’s pardons for members of the House select committee that investigated the Jan. 6, 2021, attacks on the Capitol are inv...

From March www.msnbc.com/morning-joe/...

There’s so much happening right now, I thought I’d put together a running thread on the dismantling of #climate and research and knowledge infrastructure in the United States 🧵

Criticizing words like “gap” and “novel” doesn’t make much sense because those are things the journal explicitly wants. It’s just good writing to say “here’s the part you’re looking for.”

No Straight Road Takes You There by Rebecca Solnit review – an activist’s antidote to despair Hope is no casual platitude in this inspiring collection of essays; it’s the realistic mindset with which to approach existential challenges

"Uncertainty is the most rational position to embrace, and unlike optimism or pessimism, it does not entrench us in complacency or inaction."

No Straight Road Takes You There by Rebecca Solnit review – an activist’s antidote to despair @theguardian.com @rebeccasolnit.bsky.social

Hard to imagine two worse examples for any apparent shift.

I agree, they do not suck and are useful. However, they unintentionally can be extremely misleading. No fact finding should be done with them unless the user is qualified to independently verify the claims. They are absolutely *not* trustworthy tools by the NIST guidelines.

#CausalityCrisis

We face increasingly serious crises due to lack of incorporation of causality into political structures and processes, more simply, inadequate policy-making, including election of policy makers ... something like that

Just imagine the times of night spent writing them

Looks like a google scholar results page

(Or as likely to)

I’m no linguist, but this seems like a great analogy for all machine learning. I don’t think it’s impossible for an ML model to capture the true underlying structure (as a universal function approximator), but it is generally unlikely. It’s harder to say if LLMs are capable of modeling langue.

By that logic, if money markets or CDs were the hip place to put savings then Harris would have won. We can’t excuse young men’s votes because they don’t understand how to invest (or get a free bank account).

Unadulterated racism.

It’s really unfortunate that this is the generous interpretation and also most likely

That the real challenges are rarely in the work itself but navigating the administrative, political, and funding mazes. I’ve found most people who drop out did not do so for academic reasons, but because of either life changes or some intolerance for the BS in the system, and they’re rarely wrong.

Computers are accusing humans of terrorism

And I think “investors” rarely expect them to grow value but often find it funny when they do. Doge is an example.

As an AI researcher like the ones you called out, that was truly unexpected and appreciated. There is strong interest in certain domains (generally only publicly funded) to make AI that supports humanity in transparent, trustworthy ways that don’t erode our social structures.

It’s late at night. But I’ve got to say this. We can endure. This is by far not the worst that has happened to a country, or even in ours. But it will take a broad and committed movement. I am confident.

Where’s a good starting point for reading statisticians directly addressing causality?

The destruction to NNSA says it all: it’s destruction for destruction’s sake. No institution is safe for any reason.

Modern conservatism in a nutshell