andrew 🇺🇦

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andrew 🇺🇦

andrew 🇺🇦

@AndrewLys3

(Fin) Math and stuff @ ncsu formerly @ uchi

Raleigh, NC Katılım Kasım 2013
268 Takip Edilen38 Takipçiler
Moe Nadim
Moe Nadim@theoneandmoely·
@saltwatersoph You can work in finance or financial services as an econ grad without needing to do quant stuff.
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sophie
sophie@saltwatersoph·
I would go back and tell 17 year old me that she should actually just try to become a quant
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andrew 🇺🇦
andrew 🇺🇦@AndrewLys3·
@constans Tbf it’s not fully free tuition, it’s partial. But still it’s crazy
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constans
constans@constans·
It blows my mind that the country whose capital is one of the world’s major financial centers finds an upper middle class American salary to be beyond the imagination
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stath
stath@stathx·
@mouse_math measure theory and functional analysis
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aashiq
aashiq@aashiq·
@mouse_math Measure Theory. Tedious, not much benefit over everyday intuition except in exotic corner cases, limited application in other branches of math.
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Samuel Watling
Samuel Watling@watling_samuel·
Econometrics is good autism, micro theory was good autism until Bayesian persuasion then it became bad autism. IO is normal autism. Econ History will be the most autistic when the methodology catches up. Politica is still a bit too relevant. The rest are more ADHD-coded.
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Samuel Watling
Samuel Watling@watling_samuel·
Due to my autistic desire to rank everything here is my list of Econ subfields ranked by autism level: 1. Econometrics 2. Pure Micro Theory 3. IO/Trade 4. Econ History 5. Political Economy 6. Applied Micro 7. Macro 8. Development 9. Behavioural
Samuel Watling@watling_samuel

@eashwarnagaraj @elisaxchen Imo Dev econ is the least autistic of all economics subfields

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Anti-Jungian Aktion
Anti-Jungian Aktion@Carboniferoys·
When ever I see one of these I do wonder what actual books would have a 130+ average IQ reader. I'd imagine the really obscure expensive and relatively new graduate level textbooks in Math/Physics might be basically it.
anathemenon@onomatopoeiatwt

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andrew 🇺🇦
andrew 🇺🇦@AndrewLys3·
@tomsteyerstan We just have to move away from single representative districts and embrace proportional representation (or some other alternative system)
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Tom Steyer Stan 🌊
Tom Steyer Stan 🌊@tomsteyerstan·
let’s check in on the state of the gerrymandering war
Tom Steyer Stan 🌊 tweet media
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Sami Gold
Sami Gold@souljagoyteller·
DC residents: where do you guys go out for the night? Gonna be here in the summer for the first time, so I’m trying to learn the tricks of the trade
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Alexey 🌅
Alexey 🌅@ferocitq·
started watching invincible and this must be the most auraless sauceless introduction to a super group ive ever seen
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andrew 🇺🇦
andrew 🇺🇦@AndrewLys3·
Streets is saying they uncovered a holy portal in Dagestan but the Russians are covering it up
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andrew 🇺🇦
andrew 🇺🇦@AndrewLys3·
@arnie_hacker hahaha i've been using colab for a couple of weeks and it's the worst thing ever when you have a server die in the middle of hte night
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Arnie Ramesh
Arnie Ramesh@arnie_hacker·
Are ML researchers constantly sleep deprived because they're trying to submit all their jobs before they sleep
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andrew 🇺🇦
andrew 🇺🇦@AndrewLys3·
@kiyodia The whole comic fire and shadow is about the fire nation not rocking with zuni
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dia 🂱 watching tlok
dia 🂱 watching tlok@kiyodia·
oh…so the fire nation is not rocking w fire lord zuko i see
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andrew 🇺🇦
andrew 🇺🇦@AndrewLys3·
Imagine going summer time driving with buckshot and fake mink
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Alexander Terenin
Alexander Terenin@avt_im·
@RobertoDailey1 For time series, GPs have been scalable since long before any of the works I've mentioned - via state-space methods which leverage higher-order Markovianity. Like in general, I expect the thing that limits performance to be expressive capacity, caused by Gaussianity itself.
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Swann Marcus
Swann Marcus@SwannMarcus89·
I hate these fucking people Neither author of this article is an economist. One is a computer and information science professor and one is an MBA It’s a coding and business major predicting the macro impact of AI on the economy decades from now
Swann Marcus tweet mediaSwann Marcus tweet media
Elias Al@iam_elias1

Two economists just published a mathematical proof that AI will destroy the economy. Not might. Not could. Will — if nothing changes. The paper is called "The AI Layoff Trap." Published March 2, 2026. Wharton School, University of Pennsylvania. Boston University. Peer reviewed. Mathematically modeled. The conclusion is one sentence. "At the limit, firms automate their way to boundless productivity and zero demand." An economy that produces everything. And sells it to nobody. Here is how you get there. A company fires 500 workers and replaces them with AI. A competitor fires 700 to keep up. Another fires 1,000. Every company is behaving rationally. Every company is following the incentives correctly. And every company is building a trap for itself. Because the workers who were fired were also customers. When they lose their jobs faster than the economy can absorb them, they stop spending. Consumer demand falls. Companies respond by cutting costs — which means automating more workers — which means less spending — which means more falling demand — which means more automation. The loop has no natural exit. The researchers tested every proposed solution. Universal basic income. Capital income taxes. Worker equity participation. Upskilling programs. Corporate coordination agreements. Every single one failed in the model. The only intervention that worked: a Pigouvian automation tax — a per-task levy charged every time a company replaces a human with AI, forcing them to price in the demand they are destroying before they pull the trigger. No government has implemented this. No major economy is seriously discussing it. Meanwhile the numbers are already tracking the curve. 100,000 tech workers laid off in 2025. 92,000 more in the first months of 2026. Jack Dorsey fired half of Block's workforce and said publicly: "Within the next year, the majority of companies will reach the same conclusion." Nobody is doing anything wrong. Companies are following their incentives perfectly. That is exactly the problem. Rational behavior. At scale. Simultaneously. With no mechanism to stop it. Two economists built the math. The math leads to one place. Source: Falk & Tsoukalas · Wharton School + Boston University · arxiv.org/pdf/2603.20617

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Meggy
Meggy@igetsoinspired·
These save lives
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Gappy (Giuseppe Paleologo)
Gappy (Giuseppe Paleologo)@__paleologo·
Reading a paper on why Deep Learning works. Short answer: PAC-Bayes.
Gappy (Giuseppe Paleologo) tweet media
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