Birkir Leó (@birkirleo) 's Twitter Profile
Birkir Leó

@birkirleo

Physics undergrad

ID: 1028934511139201025

calendar_today13-08-2018 09:21:18

985 Tweet

171 Followers

1,1K Following

andi (e/alb) (@nexuist) 's Twitter Profile Photo

One thing I wish I could beat into the heads of all the CS majors that follow me is that the Silicon Valley old guard stayed up late coding on weekends not so they could get rich enough to never code again but to buy more time staying up late coding on weekends in their 50s

Tivadar Danka (@tivadardanka) 's Twitter Profile Photo

This will surprise you: sine and cosine are orthogonal to each other. What does orthogonality even mean for functions? In this thread, we'll use the superpower of abstraction to go far beyond our intuition. We'll also revolutionize science on the way.

This will surprise you: sine and cosine are orthogonal to each other.

What does orthogonality even mean for functions? In this thread, we'll use the superpower of abstraction to go far beyond our intuition.

We'll also revolutionize science on the way.
Peyman Milanfar (@docmilanfar) 's Twitter Profile Photo

Most tech people know about ordinary least-squares (OLS), but not so much about *total* least-squares (TLS) They measure fit differently: OLS minimizes sum of sq. distances along dependent variable; whereas TLS minimizes sum of orthogonal distances from data to fit line 1/2

Most tech people know about ordinary least-squares (OLS), but not so much about *total* least-squares (TLS)

They measure fit differently: OLS minimizes sum of sq. distances along dependent variable; whereas TLS minimizes sum of orthogonal distances from data to fit line

1/2
Dmitry Krotov (@dimakrotov) 's Twitter Profile Photo

Lagrangians are often used in physics for deriving the energy of mechanical systems. But are they useful for neural networks and AI? It turns out they are extremely helpful for working with energy-based models and energy-based Associative Memories. You need to specify a

Lagrangians are often used in physics for deriving the energy of mechanical systems. But are they useful for neural networks and AI? 

It turns out they are extremely helpful for working with energy-based models and energy-based Associative Memories. You need to specify a
Yi Ma (@yimatweets) 's Twitter Profile Photo

I believe all professors in the field of AI and machine learning at top universities need to face a soul-searching question: What can you still teach your top (graduate) students about AI that they cannot learn by themselves or elsewhere? It had bothered me for quite some years

Demetri Kofinas (@kofinas) 's Twitter Profile Photo

Never have I seen a more powerful engine for the redistribution of generational wealth than the combination of narrative and flow seen in crypto. If anything, my primary regret as an investor is that I could have never been bullish enough on my financial nihilism thesis.

Fed (@lord_fed) 's Twitter Profile Photo

Most traders don’t lose on bad ideas. They lose on bad execution. Part 1 was the map, this is the manual. Zero to Stock Hero: Part 2 (free) lordfed.co.uk/p/from-zero-to…

Tivadar Danka (@tivadardanka) 's Twitter Profile Photo

The single most undervalued fact of mathematics: mathematical expressions are graphs, and graphs are matrices. Yes, I know. You already heard this from me, but hear me out. Viewing neural networks as graphs is the idea that led to their success.

The single most undervalued fact of mathematics: mathematical expressions are graphs, and graphs are matrices.

Yes, I know. You already heard this from me, but hear me out.

Viewing neural networks as graphs is the idea that led to their success.
Physics In History (@physinhistory) 's Twitter Profile Photo

The de Broglie equation (λ=h/p) reveals that all matter has wave-like properties. It links a particle’s wavelength (λ) to its momentum (p=mv), with h as Planck’s constant.

The de Broglie equation (λ=h/p) reveals that all matter has wave-like properties. It links a particle’s wavelength (λ) to its momentum (p=mv), with h as Planck’s constant.
Kevin Maloney (@kevinrmaloney) 's Twitter Profile Photo

One of the best things you can do as a writer is read… not necessarily a LOT of books but deeply of a handful of authors who make you feel alive. Read all their books. Read three biographies. Read their correspondence. Read the writers that inspired them. My experience is that…

Gabbar (@gabbbarsingh) 's Twitter Profile Photo

Always thought the way Calculus is thought in School is very flawed. Alienates a lot of people. This current generation is lucky. Watch:

Finn Hulse (@finn_hulse) 's Twitter Profile Photo

one time i accidentally gave the most evil guy i know a job at IMC because i cracked his entire internship in one math problem

Yaashaa Golovanov (@golovanov_ammoc) 's Twitter Profile Photo

When two Fields Medalists, Terence Tao & Hugo Copin, declare a book a “must-read,” it is undoubtedly a masterpiece. David Bessis, a leading mathematician, invested two decades of his life to distill profound wisdom into this work, which I describe as a “scheme of mathematization”

When two Fields Medalists, Terence Tao &amp; Hugo Copin, declare a book a “must-read,” it is undoubtedly a masterpiece. <a href="/davidbessis/">David Bessis</a>, a leading mathematician, invested two decades of his life to distill profound wisdom into this work, which I describe as a “scheme of mathematization”