Injustice in Open Source

Rob Knop of Galactic Interactions has an article about misogyny in open source development.

Whereas the number of women in biology and chemistry has improved a lot in recent decades, the number of women in Physics creeps up much more slowly. Meanwhile, in computer science, the number of women has actually be declining. As for the absolute values of those numbers, one need only look at a picture of a Linux Kernel Developers' Summit to realize that within statistical uncertainty, the number of Y chromosomes is the same as the number of people in the picture.

Knop attributes this to the misguided belief of men in these fields that they are somehow smarter than the rest of the populace, and hence also smarter than women. It must be that way, because you don't see many women computer scientists, do you? It never occurs so them that their attitude might be the reason that many women don't try for a career in computer science.

While I've never worked in open source, I tend to agree with Knop's assessment. Now here's the million-dollar (or million-women working in computer science) question: How change this state of affairs?

Sure, it would be nice if open source developers would be more welcoming to women, but let's just assume that they're not that cooperative for a moment. There's certainly no way to force them, after all, these projects are their own to do with as they please. So how can women fight back?

What I would like to see is more open source projects started by women, with a quota of 50% or more women developers. Maybe a little community could spring up around it. Think of it as Sourceforge with more X chromosomes. There could be discussion forums for female software developers, and maybe a blog collecting instances of misogyny and of female successes. All it takes is a few women developers getting together, buying a couple of servers, coming up with a light-weight content management system, and you're off. No males required.

What's So Special about the Humanities?

The school finally showed some mercy and moved us to a new lecture theatre for the Probabilistic Modelling class. Not only does this mean that we no longer have to suffocate in a small room, but the new venue is also in one of the old buildings of the University.

I've very seldom been in the old buildings, with the exception of special occasions like exams and graduations. Mostly, these buildings only house the Humanities as well as the School of Law and the School of Medicine.

It's a complete change of scenery. Where we get ugly buildings from the seventies and eighties, with sparsely furnished, functional lecture theatres, the other schools are housed in huge stone buildings with marble arches, balconies and skylights. I mean, I get it, they have been around longer than Science and Engineering, but seriously, would it kill the University to at least give us some lectures in nice surroundings?

Newsflash: Earth Simulator Exists, Written in Fortran

This is hilarious: A professor from the University of Texas claims to have written a complete simulation of the planet Earth. By himself. In Fortran. Oh, and it runs in a matter of minutes. There are so many unbelievable, nay, impossible claims in his paper that it's hard to decide where to start in dissecting it. Fortunately, Marc Chu-Carroll over at Good Math, Bad Math has already done it better than I could.

I think that accomplishing that [incorporating quantum mechanics] would easily win him another Nobel prize, in addition to the Nobel for the non-quantum simulator. All he'd need to do is publish the data. Wouldn't that be a coup? A creationist professor from a diddly little school in Texas showing up all of the best and brightest physicists in the world, with something he did on a lark with one of his friends? Gosh, why do you suppose that he hasn't published this? Hasn't shown anyone the simulation? You think that maybe, just maybe, there's a reason for that?

I suppose that Granville, modest gentleman that he is, might not like the spotlight that these awards would generate. That must be why he only mentions this astonishing feat of brilliance in a piece of sloppy apologetics.

Assignment Time

I just heard that the first assignment for this year will be about spam detection. Ironically, spam detection is exactly the topic that I was looking at late last year when choosing a project for the Google Summer of Code. Now if I had actually got off my behind, put together a proposal and done that project, this first assignment might be a breeze. Oh well.

Cooking for Engineers

Ever been frustrated with imprecise recipes? A pinch of salt. What exactly is a pinch of salt? And does "whisk" mean whisking until solid, or until combined? Well, Cooking for Engineers promises to change all that with recipes made for engineers, by engineers.

Of course, we'd better hope they're not software engineers, otherwise we'd have to start cooking before we get the recipe, change ingredients after putting them in, and finish up by testing the meal on the dog.

Predicting Antibodies

Here's some interesting news from ScienceDaily: Researchers at MIT have developed a computational model that can predict how given changes to an antibody can influence its effects.

Traditionally, researchers have developed antibody-based drugs using an evolutionary approach. They remove antibodies from mice and further evolve them in the laboratory, screening for improved efficacy. This can lead to improved binding affinities but the process is time-consuming, and it restricts the control that researchers have over the design of antibodies.

In contrast, the MIT computational approach can quickly calculate a huge number of possible antibody variants and conformations, and predict the molecules' binding affinity for their targets based on the interactions that occur between atoms.

The interesting bit is the prediction. It's presumably easy enough to model changes an antibody (essentially a protein), but predicting what the new version of the antibody will do is much harder. I can't wait to read the paper.

Breasts on Facebook?

Brace yourselves. What I say next may shock you. Ready? Okay:

There were breasts on Facebook.

Don't panic! Breathe. Stay with me. The good news is, Facebook acted decisively and removed ALL of the...

Wait, hang on.

Okay, I'm being told they didn't remove all of the pictures of breasts. Apparently, they removed pictures of a woman breast-feeding and banned the woman in question from Facebook.

Now, even most prudes would find it hard to condemn breast-feeding as obscene. See, contrary to popular (read, male) opinion, breasts actually serve another purpose besides being sexually arousing. In deleting the pictures, Facebook was focusing on the nudity of said breasts, and many commentators are making the same mistake. Instead of saying "Facebook deletes pictures of woman's breasts", how about "Facebook deletes pictures of woman feeding her baby". That's all that that picture was about, a baby being fed. How much more innocuous can you get?

How Quaint

I don't know about you, but I barely remember web searching without Google. So it's kind of quaint to see the humble beginnings of Google in this paper from around 1997, The Anatomy of a Large-Scale Hypertextual Web Search Engine:

Search engine technology has had to scale dramatically to keep up with the growth of the web. In 1994, one of the first web search engines, the World Wide Web Worm (WWWW) [McBryan 94] had an index of 110,000 web pages and web accessible documents. As of November, 1997, the top search engines claim to index from 2 million (WebCrawler) to 100 million web documents (from Search Engine Watch). It is foreseeable that by the year 2000, a comprehensive index of the Web will contain over a billion documents. At the same time, the number of queries search engines handle has grown incredibly too. In March and April 1994, the World Wide Web Worm received an average of about 1500 queries per day. In November 1997, Altavista claimed it handled roughly 20 million queries per day. With the increasing number of users on the web, and automated systems which query search engines, it is likely that top search engines will handle hundreds of millions of queries per day by the year 2000. The goal of our system is to address many of the problems, both in quality and scalability, introduced by scaling search engine technology to such extraordinary numbers.

What is this "Altavista" thing they keep talking about?

Some Thoughts About Recaps

So today's course on Probabilistic Modelling started, not surprisingly, with a recap of basic probability theory. I'm not objecting to that, and there were clearly people in the class who have not done probability before. However, I had the same recap last year for a Modelling and Simulation course, and the year before that for an Artificial Intelligence course.

The repetitiveness of it got me thinking: Why waste time on all these separate recaps? Wouldn't a much more elegant solution be to organise one class of one or two hours a year which recaps probability theory, and everybody who needs it could go there?

Sure, there might be scheduling problems, but it still seems better than to subject everyone to the same recap, and force three different lecturers to teach the same material at roughly the same time. And I'm sure probability theory is not the only subject that recurs frequently in recaps.

First Impressions

The view of the city is lovely from the 7th floor of that skyscraper where our first lecture was housed. On a clear day like today, you can see all the way to the hills in the distance. I know this because I've had lectures there during my undergraduate career. I certainly didn't notice any of this today, because I was crammed into a corner of the room, trying desperately not to suffocate as more and more people piled into the room.

There are three kinds of lectures in Informatics; those that are contain so much Maths that only joint CS/Maths students take them, those that focus on cramming as much knowledge as possible into our heads, and those that don't require much Maths or knowledge, but teach us how to actually solve problems. You can probably guess which is the most popular kind.

This lecture was one of those, and despite having a certain fondness for the mathematical courses, I'm not complaining. I merely wish that, at the next lecture, there will be fewer people and more space in the room for other things. Like, for a start, oxygen.

Obligatory Introduction

If you're reading this, I can only assume that you took a wrong turn somewhere in the network of internet tubes. You misclicked, your mouse shattered on the ground, and you've ended up on my blog. Now you're staring at your screen in horror, desperately trying to remember the keyboard shortcut for the Back button.

Fear not, gentle reader. You're quite safe with me. I do not use this blog to present my Hentai collection to the world or introduce you to the latest in body modification (don't do a Google Image search!). I won't even post images of my cat, mainly because I don't have a cat. I promise that nothing on these pages will make you want to scoop your eyes out with a spork. Unless I link to Warren Ellis.

So what can you expect from this blog? Well, I am currently starting an MSc. programme with its main focus on Machine Learning at a wonderful British university, and I expect that will colour the Gaussian Noises that this blog emits. Look forward to reading about my take on current research, old ideas, and any weirdness that I might come across. Of course, I reserve the right to post off-topic once in a while. But I promise: No cats!