Monthly Archives: March 2015
The Realities of Docker in Production
“Docker seems like a fundamentally better abstraction for packaging and deploying applications in a persistent way across multiple environments. Among individual developers and ops engineers it’s praised, but at a recent Docker in Production meetup held at Heavybit, engineers from Iron.io, ClusterHQ, RelateIQ and Docker discussed the realities of running Docker in Production — namely what does and doesn’t work…”
Debugging like a sir (in C)
Peter Norvig: How Computers Learn
“Vienna Gödel Lecture 2015 with Peter Norvig, Research Director at Google Inc.”
O Simples e Elegante Algoritmo Que Torna o Google Maps Possível
“Algoritmos são uma ciência baseada em engenhosidade. Uma manifestação natural do raciocínio lógico – indução matemática, em especial – um bom algoritmo é como um retrato passageiro e condenatório da alma de um problema. Uma selva de propriedades e relações torna-se uma simples relação de recorrência, um passo recursivo de linha única produzindo caos e complexidade sem limites. E para ver através desta complexidade, é necessário engenhosidade.
Foi o pioneiro da programação Edsger W. Dijkstra quem realmente sacou isso, e o algoritmo que leva seu nome segue como uma das coisas mais engenhosas na informática. Um defensor ferrenho da simplicidade e elegância na matemática, ele meio que acreditava que todo problema complicado tinha uma parte acessível, uma entrada, e a matemática era uma ferramenta a ser usada para encontrá-la e explorá-la…”
Why Racket? Why Lisp?
“In practical programming projects, Lisps are rare, and Racket especially so. Thus, before I embarked on my Lisp adventure, I wanted to understand the costs & benefits of using a Lisp. Why do Lisps have such a great reputation, but so few users? Was I seeing something everyone else missed? Or did they know something I didn’t? To find out, I read whatever I could find about Lisps, including Paul Graham’s Hackers & Painters and Peter Seibel’s Practical Common Lisp. (OK, parts. It’s a big book.)
What I found was plenty of Lisp flattery from expert Lisp programmers. (Also plenty of Lisp kvetchery from its detractors.) What I didn’t find were simple, persuasive arguments in its favor. So here’s why Racket was the right tool for this project, and what I see as the practical virtues of Lisps in general...”
Deep Learning, NLP, and Representations
“In the last few years, deep neural networks have dominated pattern recognition. They blew the previous state of the art out of the water for many computer vision tasks. Voice recognition is also moving that way.
But despite the results, we have to wonder… why do they work so well?
This post reviews some extremely remarkable results in applying deep neural networks to natural language processing (NLP). In doing so, I hope to make accessible one promising answer as to why deep neural networks work. I think it’s a very elegant perspective…”
http://colah.github.io/posts/2014-07-NLP-RNNs-Representations/
