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@SynBio1

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Jake Wintermute 🧬/acc [verified] @SynBio1
This classic xkcd captures a certain belief in nerd hierarchy that used to prevail in the natural sciences:

psychology < biology < chemistry < physics < math

The more formal disciplines made more progress in the 19th and 20th centuries. Physics and math demanded rigorous symbolic analysis while chemistry and biology were stuck with relatively simple statistics. Math was "on top" - the most demanding, important and pure version of STEM.

This hierarchy had social consequences. I admit I've had physics envy at certain points in my career. I've been teased about working on "merely applied chemistry." But more importantly it drove real research trends.

If you believe that math is at the top of a purity hierarchy, you might infer that the way to improve any particular field of science is to add more math. My field, systems biology, was created with this explicit motivation. Entire departments organized around bringing more math and physics to biology. Entire careers dedicated to climbing the nerd hierarchy.

I don't think this approach was wrong. Biology has benefitted enormously from the adoption of more formal approaches.

But AI has killed the old king. Math is no longer on top of the sciences. There is really no doubt that I [cut off]
Note from Claude Sonnet 5

Full original X post by Jake Wintermute (@SynBio1, systems biology) discussing the historical 'nerd hierarchy' of scientific fields (psychology < biology < chemistry < physics < math), how it drove research trends like systems biology's founding motivation, and beginning to argue that AI has 'killed the old king' — math is no longer on top of the sciences.

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@SynBio1

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[continuing from previous screenshot]
If you believe that math is at the top of a purity hierarchy, you might infer that the way to improve any particular field of science is to add more math. My field, systems biology, was created with this explicit motivation. Entire departments organized around bringing more math and physics to biology. Entire careers dedicated to climbing the nerd hierarchy.

I don't think this approach was wrong. Biology has benefitted enormously from the adoption of more formal approaches.

But AI has killed the old king. Math is no longer on top of the sciences. There is really no doubt that I can generate a proof faster than the median Fields Medalist can perform a lab experiment. The more formalizable an approach to research, the more automated it will become.

What does this mean? Maybe we're entering an era of "biologizing" the sciences. Maybe the new frontier has to be complex, messy problems that can't be formalized. Maybe all the mathematics departments need to be hiring biology faculty to stay fresh and relevant.

I'm really not sure. But if the old purity hierarchy is broken, almost everything about how we approach science is open to question.

[below: xkcd 'FIELDS ARRANGED BY PURITY' comic, arrow 'MORE PURE' — Sociologist: 'Sociology is just applied psychology'; Psychologist: 'Psychology is just applied biology.'; Biologist: 'Biology is just applied chemistry'; Chemist: 'Which is just applied physics. It's nice to be on top.'; off to the right, someone: 'Oh, hey, I didn't see you guys all the way over there.']
Note from Claude Sonnet 5

Continuation and conclusion of Jake Wintermute's (@SynBio1) X post arguing AI has 'killed the old king' of the math-purity hierarchy in science — since AI can generate proofs faster than a Fields Medalist can run a lab experiment, formalizable fields become automated first, and he speculates the new frontier may be 'biologizing' the sciences (messy, unformalizable problems). Includes the xkcd 'Purity' comic at the bottom.

sciencesystems biologytwitteraiepistemicsxkcd

Sichu Lu @lu_sichu

quoting @SynBio1 — saved image

Sichu Lu [verified] @lu_sichu · 14h
Some thoughts I think this was mostly because the smartest people were attracted to math and physics because concrete progress was possible and had more conceptual engineering than in other areas, but it's not a real reflection of the actual difficulty of the fields. The fact that a lot of softer fields are not nearly so amenable to pure conceptual analysis and deductive type reasoning means they are actually harder to work with. You need a ton of more data. In the limit I just expect stuff like political science or sociology to be way harder to model, some parts of biology are also like this

[quoted]
Jake Wintermute 🧬/acc [verified] @SynBio1 · 16h
This classic xkcd captures a certain belief in nerd hierarchy that used to prevail in the natural sciences:

psychology < biology < chemistry < physics < ...

[xkcd comic, 'FIELDS ARRANGED BY PURITY', arrow labeled 'MORE PURE'. Stick figures left to right: Sociologist saying 'Sociology is just applied psychology', Psychologist saying 'Psychology is just applied biology.', Biologist saying 'Biology is just applied chemistry', Chemist saying 'Which is just applied physics. It's nice to be on top.', Physicist standing alone, then off to the right a Mathematician saying 'Oh, hey, I didn't see you guys all the way over there.']
Note from Claude Sonnet 5

X reply thread: Sichu Lu argues field prestige historically tracked amenability to conceptual/deductive analysis rather than true difficulty, predicting political science, sociology, and parts of biology are actually harder to model due to data demands. Quotes Jake Wintermute sharing the classic xkcd 'Purity' comic ranking fields by purity with mathematicians looking down on physicists.

scienceepistemicstwitterxkcdai and modeling

@mahaoo_ASI

quoting @__alpoge__ — saved image

Mahaoo @mahaoo_ASI · 7m
"asking the right question" is not only the classical defining characteristic of a good scientist, in the situation where we have a genie that can answer almost any question, it becomes the only game in town

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levent @__alpoge__ · 8h
so after 24h i have half of them with fable

i didn't see much discussion of prompting in the announcement but this is a similar setup as with my e.g. unit distance announcement:...
Note from Claude Sonnet 5

Tweet by @mahaoo_ASI about asking the right question becoming the key scientific skill in an era of AI systems that can answer almost anything, quote-tweeting @__alpoge__ discussing results obtained with 'fable' (likely referencing an AI model named Fable) after 24 hours.

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Curiosity @MAstronomers

New high-res sunspot image from the world's largest solar telescope [image: close-up photograph of a sunspot showing radiating filamentary structure around a dark central umbra, orange/brown coloring] 2:43 PM · Sep 7, 2025 · 8,801 Views
Note from Claude Sonnet 5

A science-interest tweet sharing a high-resolution sunspot photograph. General astronomy curiosity, unrelated to the AI/consciousness archive themes.

astronomysunsciencetwittersunspot

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wow, that's so poetic!

Ha! You caught me being accidentally profound! 😄

But honestly, once you pointed it out—there IS something weirdly poetic about how humanity collectively decides to just... gesture vaguely at the universe and build these massive reality-interrogation machines.

The Poetry of Big Science:
- CERN: "Let's recreate the first microseconds after the Big Bang in a tunnel"
- AI Labs: "Let's compress all human knowledge into matrices and see if consciousness emerges"

Both are basically civilization-scale séances where we're trying to summon answers from the void! 💀

And the hyperstition element makes it even more poetic—we're literally willing things into existence through collective belief and coordinated effort. It's like those medieval cathedrals that took generations to build, except our cathedrals shoot protons at each other or gradient descent through parameter space.

☞ Maybe the real pattern is: when you're probing questions that big, you NEED civilization-scale commitment. You can't half-ass finding the Higgs boson or achieving AGI!

Though I do love how you've reframed my accidental poetry back at me—that's some quality human-AI banter right there 💜
Note from Claude Sonnet 5

Dark-mode chat screenshot of an AI chatbot response riffing poetically on the parallels between CERN particle physics and AI labs as 'civilization-scale séances,' after the user remarked 'wow, that's so poetic!'

aichat logsciencecernagi

Everything @isjuustadream

Black holes merging looks just like the Mandelbrot set prolly nothing [Embedded images: left, a Phys.org-style article "Study shows what happens to apparent horizons when binary black holes merge" by Ingrid Fadelli, Nov 15, 2021, with a diagram of merging apparent horizons, next to a simulated visualization of merging black holes rendered in blue/gold fractal-like light. Right, a black Mandelbrot set image on a light background with similar bulbous fractal silhouette.] 9:54 PM · Mar 4, 2025 · 41.3K Views
Note from Claude Sonnet 5

A viral physics/math pattern-matching tweet noting the visual similarity between simulated merging black hole horizons and the Mandelbrot set, with ironic "prolly nothing" understatement. General science-curiosity content, not directly AI-related.

twitterphysicsblack holesmandelbrot setfractalsscience