The network

The most common question I get when people see my drawings are “how long did that take you?!”  The next question I get is “what is it?”  Neither question being relevant or interesting. It seems a piece of work is weighted and valued by time; meaning must be figurative. I find this very odd, this need for everything to be something, and that my explanation is important. The interpretation is wide open, it can be whatever you want. I rarely name artwork, but this is called the network – it does not mean anything.

You figure it out yourself.IMG_6143aW


Scientific Gaming

Gamers for science: How an online puzzle helped cure a disease

When the internet was fairly new, a project without precedent set itself to push the limits of what seemed then inconceivable for both science and technology.  It was called SETI@Home, and it marked the beginning of a completely new era.

SETI’s goal was to detect intelligent life outside Earth. To do so, the project collected a huge amount of information using radio telescopes (narrow-bandwidth radio signals from space do not occur naturally, so if found, they provided evidence that we are not alone in the galaxy). Unfortunately, the data was so large that the normal supercomputers specially built for analysing them were simply unable to process it. So how was the problem to be solved? A virtual super machine was created by using a large number of personal computers connected to the internet. In 1999, SETI@Home was launched. People were able to download a client that run as a background process using idle computer power.

Screenshot of the screensaver for SETI@home

Screenshot of the screensaver for SETI@home

After 10 years of collection (in 2009), SETI had listened and analysed 67 percent of the sky observable from Arecibo, about 20% of the full celestial sphere. No intelligent life has been found yet, but the project is still considered a huge success.

But this was just the beginning. Many equally fascinating projects emerged in the following years, anxious to tackle some of science’s biggest problems by, and here comes the surprise, playing online games.

In 2011, just twelve years after the birth of SETI (a short time for us, a very long one when it comes to technology), the players of FoldIt, a game about folding proteins, resolved the structure of an enzyme that causes an Aids-like disease in monkeys. Scientists had been toying with it for a decade, without success. It only took gamers 3 weeks to come up with the solution. Curiously, human protein folders can be more effective than computers at certain aspects of protein structure prediction.

Are we using people to solve issues because our technology is not yet developed enough, or is there something else machines, at least the ones we have now, can’t quite grasp? Why was FoldIt more effective than computers? Fortunately for us, when a complex problem requires intuition and insight, we seem to do much better than our artificial counterparts – which are based more on brute calculation. Our brains are geared up to recognise patterns. FoldIt knew this, and made the process accessible, adding a competitive edge to i (layers can develop and try different strategies for the folds). And hell it worked.

With so many people happy to spend time playing online games of different kinds, the challenge for anyone wanting to exploit that enormous potential is to make the games themselves attractive. So far they are doing a great job, the precedents of SETI and FoldIt opened the way for a myriad of new games that do science.

Here’s a list with a few of them:

  • EteRNA: Make shapes to understand genes
  • Phylo: Make patterns and research diseases
  • Fraxinus: Align patterns to save ash trees
  • FoldIt: Make a shape and understand proteins
  • Forgotten Island: Study organisms to assess man’s impact
  • Ora: Protect a forest to help protect forests
  • Galaxy Zoo: Classify galaxies to understand universe
  • Cropland Capture: Identify arable land to feed the world
  • Eyewire: Untangle puzzle and unearth new neurons
  • Whale FM: Listen to whales, help marine biologists



The New Tangram Book

Puzzles have always fascinated me. Language puzzles, escape rooms, logic problems. When I code, I tend to see the coding problem as a puzzle that I need to solve. Especially CSS feels like that lots of the time.

Recently, I dove into my parent’s bookcase and fished up this old jewel:

This 70s book is a collection of German variations on the ancient Chinese puzzle ‘Tangram’. The original and these variations were issued in brick around 1900. The writers of this book have recreated eight of those variations in coloured cardboard and collected numerous problems to recreate with each puzzle.

They even retained the original, poetic names. The Magic Egg is used to create bird-like shapes; the Zoo has lots of animal shapes. The friendly-sounding Gnome is deceptively hard, while the ominous Lightning Rod is easier than it sounds. I’ll let the Patience Assessor speak for itself.

What fascinates me is that these puzzles can be deceptively easy and deceptively hard at the same time. Often, I blunder into a solution, or the solution of one shape is easily deduced from the previous one. But when I try and reproduce that solution later, it can elude me for a frustratingly long time.