databuff writes: It might just be the smartest company in the world; responsible for solving some of the toughest problems ever posed — from accurately mapping Dark Matter in the Universe to how to avoid buying dodgy vehicles at a used car auction. Kaggle – a collection of more than 17,000 PhD-level brains who compete for prizes in solving incredibly complex questions – is using the power of the internet to accelerate problem solving on a massive scale. Essentially, it's crowd sourcing for geniuses.
databuff writes: For a decade, the world's brightest physicists have been working on understanding and mapping dark matter. On May 23, a consortium including NASA, the European Space Agency and the Royal Astronomical Society, opened up the problem on Kaggle, a platform for machine learning competitions. To detect the presence of dark matter, the consortium asked entrants to build algorithms that detect a phenomenon called gravitational lensing, which causes distortions in the shape of a galaxy. In less than a week, Martin O'Leary, a PhD student in glaciology from Cambridge University made a breakthrough, outperforming the most commonly used algorithms in astronomy. O'Leary applied techniques common in glaciology, to detect the edges of glaciers from satellite images. As profound as the breakthrough is for cosmology, this competition is a prime example of how harnessing interdisciplinary approaches can help make significant scientific discoveries.
databuff writes: The April 4 launch of the $3 million Heritage Health Prize was just announced by the Heritage Provider Network, a network of doctors. The competition challenges data hackers to build algorithms that predict who will go to hospital in the next year, so that preventative action can be taken. An algorithm might find that somebody with diabetes, hypertension and high cholesterol is a 90 per cent risk for hospitalization. Knowing this, it might be cheaper for an HMO to enrol them in an exercise program now rather than pay the likely hospital bill. The competition takes the same approach as $1 million Netflix Prize, but solves a far more significant problem.
databuff writes: The Elo rating system was invented half a century ago by Hungarian physicist and chess master Arpad Elo. It is used throughout the chess world and has been applied to other contests, ranging from World of Warcraft to soccer. However, Elo's formula was derived theoretically, before we could easily crunch large amounts of historical data — so it is likely that modern approaches could do much better. Jeff Sonas, the creator of the Chessmetrics system, has just launched a competition to find a superior chess rating system. Competitors build their rating systems based on the results of more than 65,000 historical chess games. They then test their algorithms by predicting the results of another 7,810 games. Entries to the competition are benchmarked against Elo as well as other well-known rating systems (such as Glicko and Chessmetrics).