'What is good mathematics?' - Terence Tao (2007, PDF): arxiv.org/pdf/math/0702396

Stephen Boyd, on the practical value of a training in math, with lessons for building software. "In my opinion, the real value of math in applied settings, ... is it gives you clarity of thought. Here we are in Silicon Valley ... I could get one team, and say, 'go build this thing.' With a lot of high-level tools now, you can bang something together that looks like it's working ... But there's another style that's just beautiful. People who think about it very deeply, often trained in math or something abstract, they don't do anything for a day or two. [Then] they look up and go, 'The 87 things we've been asked to implement are actually all instances of only 3 different things. So we're going to implement [those 3 things] correctly.' When people just hack something together to knock off 87 requirements, it's going to be horrible code, badly structured, ... it won't be correct ... you definitely won't be able to extend it. Whereas when you see people who think abstractly, and took the time to work out the correct abstractions, you get beautiful lean code that has very high probability of being correct. As a purely practical matter, the cost of ownership of that project is a lot less because it will work, and it's extensible and maintainable. It's like Linux, for example. That's a good model for this."

Our next Robust Optimization Webinar will take place this week Friday, February 24 at 15:00 (CET) via Zoom. Speaker: @dbertsim (Massachusetts Institute of Technology) Title: Robust Optimization with Information Theory Inspired Uncertainty Sets and its Applications #ROW

En el XIX, Chicago sufrió graves problemas de salubridad, pues su alcantarillado vertía al mismo lago del que luego bebían. Lo solucionaron con una obra brutal: HICIERON QUE EL RÍO CORRIESE HACIA ATRÁS. En #LaBrasaTorrijos de hoy, cuando el río Chicago se dio la vuelta. 🧵⤵️

Usher for academics, a 🧵:

The rest of the proof: 👍🏽 Jensen’s Inequality:

I asked, “What is the single product that’s had the biggest impact on your health and wellness?” I received 1,718 incredible replies. Here are the 10 best:

Parents have to choose their battles. 8 fights worth picking with your kids:

In 1994, Jeff Bezos famously spotted a stat that made him leave his high-paying PE job to start Amazon: 💡 The Internet was growing 2300% per year. What are the generation-defining stats of today? I'll post a few to kick things off...

🔟 Engineering graduate students earn prestigious Presidential Fellowships! Congrats to Ana, Surya, Nina, Gonzalo, Julio, Başar, Deb, Junao, Simin & Menglin 👏🏾👏🏼👏🏽👏🏿👏🏻 engineering.osu.edu/news/202…

Here's @ylecun in 1993(!) demoing LeNet-1. This was the world's first convolutional neural network for handwriting recognition. Today—29 years later—this same approach powers the majority of computer vision. Such a historical moment, and breakthrough for machine learning.

This is what it took me until my last year of grad school to realize. I’m still regularly overwhelmed by how much I don’t know, but I no longer suffer from the delusion that everyone else in my position knows 5x more than me.

Today the videos that I made to accompany my book Linear Algebra Done Right surpassed two million minutes of total viewing on YouTube. Those videos are freely available from the links at linear.axler.net/LADRvideos.…. #LinearAlgebra

Volcán Cotopaxi reflejado en la Laguna Santo Domingo. No tengo ningún pacto, a veces las estrellas no quieren asomar para la foto.

🔲 ⭕️🔺 Lin Yung Cheng

Two updates (mostly for PhD students) as you may like to plan from now: 1- I will run my online 3-week PhD course (lnkd.in/gw9Be9A) again in January 2022. The video lectures of the last edition are available here: lnkd.in/d8ZawMi 2- See below:

Come one, come all! Seriously, Columbus, OH is a great town that is family friendly with the best zoo @ColumbusZoo hockey @BlueJacketsNHL science museums @COSI soccer @ColumbusCrew hiking (Hocking Hills) apple picking (Lynd Fruit Farm) and so much more!

Accomplishing next to nothing, the grad student is still exhausted.

Principal Component Analysis is one of the most fundamental techniques in data science. Despite its simplicity, it has several equivalent forms that you might not have seen. In this thread, we'll explore what PCA is really doing! 🧵 👇🏽