Category Archives: computing

Programmer’s lament

“Since I’ve violated the Golden Rule of Helping Friends with their PC Problems and attempted to help a friend with his PC problem, expectedly wiping out his hard drive in vain, I had many opportunities to explain the Programmer Paradox: how can a programmer fail to make a computer do as he wishes? While the difficulty of debugging a program without the source proved hard to explain to laymen, I think I’ve found a metaphor that does a good job. A programmer is to the blue screen of death what Mikhail Kalashnikov is to a loaded AK-47: just as helpless a victim as any other mortal, except for having a profound understanding of the mechanisms of his execution.”

Yossi Kreinin

New site launched today:

I launched a new site site this morning:

I saw this xkcd comic recently, and it made me want to be able to see Wikipedia articles side-by-side with their “simple” counterparts.

Simple English Wikipedia is a version of the Wikipedia encyclopedia, written in Simple English and started in 2004. The encyclopedia is supposed to be used by children, who might not understand the complicated articles in the English Wikipedia, and other people who are still learning English.” is a quick hack I put together that lets you view the articles side-by-side. To do this, go to the site and type an article name in the search box (for example, War, or Peace, or Chocolate). Or, paste the article’s URL directly from wikipedia (for example, Then click the “Again, but slower” button. The site will try to load the original article and the simplified article side-by-side. If it doesn’t find the simple version, try a different article, because not all of Wikipedia’s articles have been translated into simple versions.

You can also try some examples by choosing one from the pulldown list on the page. Or, try your luck with a random article by clicking the Random button. If you click the full formatting checkbox, the original formatting of the Wikipedia articles will be displayed (the site displays the printable stripped-down format by default).

links for 2009-03-06: Pile o’ toys

This impressive augmented reality demo from GE inserts computer-generated 3D objects into live video. First, watch the short video. Then, try it yourself.
Israeli musician “Kutiman” took a big pile of seemingly random YouTube video clips and used them as instruments in his own musical compositions. I could not stop listening to these. My favorites are tracks 2 and 3. His site is overloaded at the time of this post; for now you can see samples here, here, and here.
Can you be an awesome DJ using nothing but a web browser and your computer’s keyboard? Yes you can.
A curious programmer, inspired by Roger Asling’s evolution of the Mona Lisa, asks if the technique could be a good way to compress images. Also take a look at the nice online version of the image evolver he wrote, in which you can set your own target image.
Hilarious Livejournal diary done in the style of Rorschach from the Watchmen comic book series.
The Crisis of Credit, Visualized – An extremely well-produced video describing the credit crisis in simple terms. – “Netflix for impatient people”. A remix of the Netflix site that is “about a quadrillion times easier to browse than Netflix’s own site”.
$timator: How much is your web site worth?
Cursebird. A real time feed of people swearing on Twitter. THANK YOU, INTERNET!
Leapfish. An interesting new meta-search engine with a clean interface. “It’s OK, you’re not cheating on Google.”
Twittersheep. “Enter your twitter username to see a tag cloud from the ‘bios’ of your twitter flock.”
PWN! YouTube. This is a great idea. You just type “pwn” in front of “youtube” in the URL, and voila; instant links for downloading and saving the videos.

User Interface Candy

Microsoft showed this “view of the future” in a presentation at a recent business technology conference:

<a href=";playlist=videoByUuids:uuids:a517b260-bb6b-48b9-87ac-8e2743a28ec5&#038;showPlaylist=true&#038;from=shared" target="_new" title="Future Vision Montage">Video: Future Vision Montage</a>

(video link)

C’mon, people; hurry up and build these awesome user interfaces! A keyboard and mouse can only do so much.


Simulated evolution parlor tricks

Here are some interesting tidbits of evolutionary computing to honor Darwin’s birthday yesterday:

Evolution of Mona Lisa

(youtube link)

Roger Alsing’s idea is to start with a random pile of polygons. Random mutations are applied to the polygons. The result is compared to the Mona Lisa source image, and mutations resulting in improvements are kept. Over many generations, the evolved image begins to resemble the Mona Lisa.

This particular application of genetic algorithms is very popular. See what many other people have tried.


This site evolves music by generating loops randomly from sounds and effects. Listeners to the site’s audio streams rank the results, and the genetic algorithm creates “baby loops” for the listeners to rank.

CSS Evolve

This site shows you variations of a web site’s cascading style sheets. You pick the best results, and their genetic algorithm breeds them to create new styles for the web site.

Automatic programming for the lazy

You never know… a random walk may lead to serendipity.

Today’s xkcd comic is well-timed because just yesterday I sent out an announcement of the availability of my implementation of Cartesian Genetic Programming for ECJ, a Java-based evolutionary computing software framework. Genetic programming (GP) is a problem-solving technique in computer science that is inspired by evolution in biology. You start with a population of randomized computer programs and measure the “fitness” of each program. The fitness is a measurement of how well a program solves a particular problem. You can think of the program itself as the “gene”.

In this simulation of evolution, the best programs in the bunch are selected for “breeding” for the next generations. Breeding is done by exchanging pieces of genetic material – in this case, we exchange pieces of the computer programs themselves. Good programs have different parts that are useful, and these parts are combined or exchanged in new “child” programs that are even better than their parents. Then, every so often, random mutations are introduced into the programs to promote diversity. Good mutations survive to future generations, and bad ones die out.

Parent programs producing offspring by exchanging pieces of themselves. Credit: Michael Adam Lones, Enzyme Genetic Programming

This sounds like a completely random way to solve a problem, but it is surprisingly effective for many kinds of problems, such as learning mathematical expressions that can describe some data set, discovering winning game-playing strategies, making forecasts and predictions from data sets, learning decision trees to classify data, evolving emergent behavior, and optimization of complex systems. Of great interest to me in applying genetic programming is the emergence of unique and fascinating solutions that are not likely to be conceived by human minds.

Cartesian Genetic Programming (CGP), the genetic programming technique I implemented for ECJ, is a variation of genetic programming invented by Julian Miller. CGP uses simple lists of numbers to represent the programs (most GP implementations use some kind of explicit tree representation). It has some interesting benefits over traditional tree-based genetic programs, such as improved search performance, reduced overhead, and less “bloat” in generated programs. My implementation includes some sample problems: regression (fitting a bunch of data to an equation), classification (identifying a species of iris flower based on simple measurements of its parts, or predicting if a breast cancer tumor will be benign or malignant), and parity (counting the number of “on” bits in a binary string).

The iris classification problem is a classic machine learning problem, dating all the way back to 1936. You have a set of measurements taken from various kinds of iris flowers, and your task is to figure out which species it is: iris virginica, iris versicolor, or iris setosa.

From left to right: iris virginica, iris versicolor, and iris setosa.

Starting with randomized programs, one of my CGP tests evolved the following programs (expressions) which correctly classified about 95% of the irises:

virginica = nand (> (- (+ 1.7777395 (/ sepalwidth sepallength)) (if 0.0053305626 petalwidth -0.6896746)) (/ -0.8330147 (neg 1.6308627))) (- (* (+ (- (+ 1.7777395 (/ sepalwidth sepallength)) (- petallength petalwidth)) 1.7777395) (- petallength petalwidth)) petalwidth)

versicolor = * (nand (> (- (+ 1.7777395 (/ sepalwidth sepallength)) (if 0.0053305626 petalwidth -0.6896746)) (/ -0.8330147 (neg 1.6308627))) (- (* (+ (- (+ 1.7777395 (/ sepalwidth sepallength)) (- petallength petalwidth)) 1.7777395) (- petallength petalwidth)) petalwidth)) (- (+ 1.7777395 (/ sepalwidth sepallength)) (- petallength petalwidth))

setosa = - (+ 1.7777395 (/ sepalwidth sepallength)) (- petallength petalwidth)

I don’t expect you to be able to read and understand the expressions – they are in a format that isn’t easy to read! What’s more important is that I didn’t have to create them myself – the CGP algorithm discovered them for me using only the input data (iris measurements) and the fitness function (a measurement of how many irises were correctly identified).

CGP also had good results when I tested the Wisconsin breast cancer data set. This data set contains measurements taken from fine needle biopsies of suspicious breast lumps. Our task is to predict whether the lumps are benign or malignant using only the measurements.

Fine needle aspiration. A thin needle is used to sample material from a suspicious lump in a breast. The data set contains the microscopic measurements taken from the sampled material.

CGP evolved the following program that correctly diagnoses the tumors 95% of the time:

malignant = not (nor (+ (+ (* cellShapeUniformity 1.5756812) bareNuclei) (<= (> (= cellSizeUniformity 0.08695793) -1.9803793) normalNucleoli)) (nor (> (- (iflez (if blandChromatin mitoses 0.75769496) bareNuclei normalNucleoli) (* 1.97491 (+ cellSizeUniformity clumpThickness))) (> 0.08695793 singleEpiCellSize)) (nor (>= marginalAdhesion (not (- (= (> (or clumpThickness 1.5756812) (= cellSizeUniformity 0.08695793)) (+ cellSizeUniformity clumpThickness)) (* (* 1.97491 (+ cellSizeUniformity clumpThickness)) mitoses)))) (iflez (if blandChromatin mitoses 0.75769496) bareNuclei normalNucleoli))))

Again, using only a fitness function and some test data, we are able to evolve a highly accurate cancer diagnosis tool.

Seems too good to be true? Well, it can be. Overfitting is a big problem when evolving these kinds of classifiers. For example, if each of the malignant tumor patients happened to be wearing red shoes during the biopsy (and the shoe type was included in the data set), a machine might be inclined to think that wearing red shoes was what determined the diagnosis. So, the evolved classifier is going to be very sensitive to whatever data set you unleash it upon.

Oh and then there’s the whole “no free lunch” thing. But that’s a depressing topic for another time.

If you want to find out more about my CGP implementation, check out the documentation. If you want to give it a whirl yourself, grab the distribution (you need at least Java 1.5). Check out the ECJ project page for more info about the evolutionary software framework my CGP implementation uses.

links for 2008-12-10

Give Up and Use Tables
"We've scientifically determined the max amount of time that you should need to make a layout work in CSS: 47 minutes. When your time is up, we'll even give you the table code you need. Take 3 minutes to build a table. Bill the client for an hour. Done."

reCAPTCHA: Stop Spam, Read Books
This is an interesting idea: Digitize books by filling out CAPTCHAs (those cryptic words you have to type in to prove you are a human being)

"Prop 8 – The Musical" starring Jack Black, John C. Reilly, and many more… from FOD Team, Jack Black, Craig Robinson, John C Reilly, and Rashida Jones
Very funny. And Jack Black is the bestest Jesus ever.

Redneck Cars: A Gallery |
My favorite is the car fitted with semi exhaust pipes.

How to bend SQL to the whims of geekery

This is even geekier than plotting the Mandelbrot set on a TI-85:

The T-SQL Mandelbrot

T-SQL is a database-centric programming language for Microsoft SQL Server. It is used primarily for data processing, not for such geekery as drawing fractals. So, my hat’s off to the creative re-imagining of this previously dull language.

(see also)

links for 2008-11-14

Take Stanford’s iPhone Programming Class For Free
– I would love to take this class. The internet-connected iPhone’s multi-touch interface and powerful multimedia features provide an amazing playground for programmers, if you can stomach Apple’s strong-armed policies on application distribution in the App Store. (BTW here is a site that tracks activity of iPhone apps in the App Store, and posts information about apps that aren’t yet available in the App Store:

bitalizer – bending bits into structure – Upload a file, and this site will turn its binary contents into a simple set of rules governing an interesting image rendering process.

Bitalizer v1.1 – shell32.dll from Brian Reavis on Vimeo.

A visualization of the bits that make up the common “shell32.dll” library file found on Windows machines.

The Pomegranate Phone – A really well-done marketing campaign for a new touch-screen GPS-enabled smartphone that also makes coffee, projects video, instantly translates your voice into other languages, has a built-in shaver, and works as a harmonica. And doesn’t really exist. Instead, it is an elaborate ad campaign created by the Nova Scotia government to generate interest for the Canadian province. The little videos included in the ad are a good touch.

Child’s Play Charity – Donate games to sick children – For my birthday, Chris and Angel donated video games in my name to a Roanoke hospital using this site. Terrific idea!

As real as it gets – This is what Photoshop would look like if it were made out of the physical world.

Frequently Forgotten Fundamental Facts about Software Engineering – A coworker sent me this great list. It was originally published in 2001 and its tenets remain true today.

In closing, a silicon haiku from our IRC robot:

like stars winking out
the woman has lost her screen
opening your toad

links for 2008-10-24

My auto-posting doodad no longer works. Automation has failed me. *Cry*.

So, here are some hand-cranked, slow-cooked links for today.

X-rays detected from Scotch tape. Incredible. Maybe somebody will exploit this to take a peek inside of Christmas presents.

How the Weird Mars Science Laboratory Floating Sky Crane Works. Very cool video showing the landing procedure of an upcoming Mars mission. GET YOUR ASS TO MARS!

ALIPR – Automatic Photo Tagging and Visual Image Search. Free photo auto-tagging service. I had very mixed results on the few tests I attempted.

Cockroach inspired robot from CWRU’s biorobotics lab. More roachbots are coming. And your sprays will not help you.

Housing prices infographic.

The bursting housing bubble is painfully clear in this graph. I’ve heard some projections that the retraction in housing prices won’t bottom out until 2011.