daniel shiffman

Just wanted to give a quick plug to ITP student Sinan Ascioglu’s new site: www.openprocessing.org — a community “flickr-like” site for Processing sketches. It’s terrific work and I’m hoping students in my courses will find it helpful for organizing portfolios of their work. I’m hoping to be able to help Sinan by figuring […]

The ITP Show finished up with some nice write-ups on the internets: ny times blog and MAKE.
About a week or so before the ITP show, my Big Screens class had their own show at the IAC Building on their rather large video wall. I’m hoping we set the world record for largest Processing sketch […]

ITP Big Screens Testing Round 2 from shiffman on Vimeo.
Project credits: http:itp.nyu.edu/bigscreens/

ITP Big Screens @ IAC from shiffman on Vimeo.
My class went to test their projects on the IAC video wall this week. The works in this video are by Young Cho, Hye Ki Min, and Ji-Sun Lee. The pieces in the photos below are by Daniel Liss and Lucia Jeesun Lee. All 15 […]

How to connect to Processing from a phone call:
http://www.shiffman.net/p5/asterisk

Calling Processing again from shiffman on Vimeo.
Going to write this up and publish the code (in conjunction with my Big Screens course) in the next couple days.

1-800-Processing from shiffman on Vimeo.

I’m pleased to announce that we’re releasing the first version of The Most Pixels Ever, an open-source Java framework for spanning Processing sketches across multiple screens (developed with Chris Kairalla). This is an early version that has many limitations and needs a great deal of improvement, but it does work. The site isn’t […]

Click to WatchWorking on a demo for the MPE system consisting a grid of cells, each playing the film Run Lola Run at 60×32 pixels. Each cell is one frame behind (or ahead) of its left (or right) neighbor. The idea here is to ultimately have enough pixel space to display the entire […]

Simple EcoSystem
This week, in The Nature of Code, we’re talking about genetic algorithms. A genetic algorithm is a search technique that involves a simulated population of candidate “solutions” (represented by virtual chromosomes) that evolve towards an optimal state. The process is a computational model of principles from biological evolution, such as […]