Slashdot Mirror
Domain: kaggle.com
Stories and comments across the archive that link to kaggle.com.
Stories · 14
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The New AI: Where Neuroscience and Artificial Intelligence Meet
An anonymous reader writes "We're seeing a new revolution in artificial intelligence known as deep learning: algorithms modeled after the brain have made amazing strides and have been consistently winning both industrial and academic data competitions with minimal effort. 'Basically, it involves building neural networks — networks that mimic the behavior of the human brain. Much like the brain, these multi-layered computer networks can gather information and react to it. They can build up an understanding of what objects look or sound like. In an effort to recreate human vision, for example, you might build a basic layer of artificial neurons that can detect simple things like the edges of a particular shape. The next layer could then piece together these edges to identify the larger shape, and then the shapes could be strung together to understand an object. The key here is that the software does all this on its own — a big advantage over older AI models, which required engineers to massage the visual or auditory data so that it could be digested by the machine-learning algorithm.' Are we ready to blur the line between hardware and wetware?" -
Website Pitches Scientific Solutions In Search of Problems
ananyo writes "In this age of social media, innovators eager to develop high-tech products are tapping into the wisdom of crowds to solve problems, with crowdsourcing sites such as Innocentive and Kaggle offering cash prizes for answers to science or data questions. The launch this week of a site called Marblar is turning this model on its head. Marblar gives scientists a space to tout solutions that have yet to find their problem (it's not in beta, despite the redirect). Members, who can come from any background, are invited to publicly discuss potential uses for patented discoveries made in research laboratories that as yet may not have led to real-world applications. Every suggestion at Marblar is posted on a public forum alongside video interviews with the scientists and explanations of their work. Website visitors suggest applications and vote them up and down, and the scientists behind the discovery are encouraged to take part in the discussion. Popular suggestions are recognized with a points system (denoted by marbles — hence the name) and, in some cases, small cash prizes. A trial run seems to have been pretty successful." -
Aussie Government Competition To Predict Commute Times
databuff writes "Last week, Sydney's Minister of Roads, David Borger, launched a $10,000 competition to develop an algorithm that predicts commute times on a major Sydney freeway. The winning algorithm will be used to power predictions on the Sydney live traffic website. The hope is that the predictions will help commuters make informed decisions about when to travel and on what routes, lowering the intensity of peak hour traffic. In its first week, the competition attracted entries from more than 50 teams and 19 countries." -
Aussie Government Competition To Predict Commute Times
databuff writes "Last week, Sydney's Minister of Roads, David Borger, launched a $10,000 competition to develop an algorithm that predicts commute times on a major Sydney freeway. The winning algorithm will be used to power predictions on the Sydney live traffic website. The hope is that the predictions will help commuters make informed decisions about when to travel and on what routes, lowering the intensity of peak hour traffic. In its first week, the competition attracted entries from more than 50 teams and 19 countries." -
Elo Chess Rating System Topped By Proposed Replacements
databuff writes "About six weeks ago, Slashdot reported a competition to find a chess rating algorithm that performed better than the official Elo rating system. The competition has just reached the halfway mark and the best entries have outperformed Elo by over 8 per cent. The leader is a Portuguese physicist, followed by an Israeli mathematician and then a pair of American computer scientists." -
Elo Chess Rating System Topped By Proposed Replacements
databuff writes "About six weeks ago, Slashdot reported a competition to find a chess rating algorithm that performed better than the official Elo rating system. The competition has just reached the halfway mark and the best entries have outperformed Elo by over 8 per cent. The leader is a Portuguese physicist, followed by an Israeli mathematician and then a pair of American computer scientists." -
Chess Ratings — Move Over Elo
databuff writes "Less than 24 hours ago, Jeff Sonas, the creator of the Chessmetrics rating system, launched a competition to find a chess rating algorithm that performs better than the official Elo rating system. The competition requires entrants to build their rating systems based on the results of more than 65,000 historical chess games. Entrants then test their algorithms by predicting the results of another 7,809 games. Already three teams have managed create systems that make more accurate predictions than the official Elo approach. It's not a surprise that Elo has been outdone — after all, the system was invented half a century ago before we could easily crunch large amounts of historical data. However, it is a big surprise that Elo has been bettered so quickly!" -
Chess Ratings — Move Over Elo
databuff writes "Less than 24 hours ago, Jeff Sonas, the creator of the Chessmetrics rating system, launched a competition to find a chess rating algorithm that performs better than the official Elo rating system. The competition requires entrants to build their rating systems based on the results of more than 65,000 historical chess games. Entrants then test their algorithms by predicting the results of another 7,809 games. Already three teams have managed create systems that make more accurate predictions than the official Elo approach. It's not a surprise that Elo has been outdone — after all, the system was invented half a century ago before we could easily crunch large amounts of historical data. However, it is a big surprise that Elo has been bettered so quickly!" -
World Cup Forecasting Challenge For Quants
databuff writes "As a break from projecting the strength of subprime mortgages, credit default swaps, and other obscure financial instruments, quantitative analysts at Goldman Sachs, JP Morgan, UBS, and Danske Bank have modeled the 2010 FIFA World Cup. Now Kaggle has set up a forecasting competition, allowing statisticians to go head-to-head with these corporate giants. The challenge is to predict how far each country will progress in the tournament." -
World Cup Forecasting Challenge For Quants
databuff writes "As a break from projecting the strength of subprime mortgages, credit default swaps, and other obscure financial instruments, quantitative analysts at Goldman Sachs, JP Morgan, UBS, and Danske Bank have modeled the 2010 FIFA World Cup. Now Kaggle has set up a forecasting competition, allowing statisticians to go head-to-head with these corporate giants. The challenge is to predict how far each country will progress in the tournament." -
Crowdsourcing HIV Research
biolgeek writes "In recent years, HIV has been managed with a collection of therapies. However, the virus will likely evolve around these drugs, making it crucially important to get a better understanding of the virus itself. An important step in understanding the virus is to get a handle on its genetic blueprint. William Dampier of Drexler University is taking a novel approach to this research by crowdsourcing his problem. He is hosting a bioinformatics competition, which requires contestants to find markers in the HIV sequence that predict a change in the severity of the infection (as measured by viral load). So far the best entry comes from Fontanelles, an HIV research group, which has been able to predict a change in viral load with 66% accuracy." -
Crowdsourcing HIV Research
biolgeek writes "In recent years, HIV has been managed with a collection of therapies. However, the virus will likely evolve around these drugs, making it crucially important to get a better understanding of the virus itself. An important step in understanding the virus is to get a handle on its genetic blueprint. William Dampier of Drexler University is taking a novel approach to this research by crowdsourcing his problem. He is hosting a bioinformatics competition, which requires contestants to find markers in the HIV sequence that predict a change in the severity of the infection (as measured by viral load). So far the best entry comes from Fontanelles, an HIV research group, which has been able to predict a change in viral load with 66% accuracy." -
A Crowdsourcing Project To Make Predictions More Precise
databuff writes "Predictions are critical to modern life. Police predict where and when crimes are most likely to take place, banks predict which loan applicants are most likely to default, and hotels forecast seasonal demand to set room rates. A new project called Kaggle facilitates better predictions by providing a platform for forecasting competitions. The platform allows organizations to post their data and have it scrutinized by the world's best statisticians. It will offer a robust rating system, so it's easy to identify those with a proven track record. Organizations can choose either to follow the experts, or to follow the consensus of the crowd — which, according to New Yorker columnist James Surowiecki, is likely to be more accurate than the vast majority of individual predictions. The power of a pool of predictions was demonstrated by the Netflix Prize, a $1m data-prediction competition, which was won by a team of teams that combined 700 models. Kaggle's first competition is underway, and it is accessing the 'wisdom of crowds' to predict the winner of this May's Eurovision Song Contest." Understandably, participation requires registration. -
A Crowdsourcing Project To Make Predictions More Precise
databuff writes "Predictions are critical to modern life. Police predict where and when crimes are most likely to take place, banks predict which loan applicants are most likely to default, and hotels forecast seasonal demand to set room rates. A new project called Kaggle facilitates better predictions by providing a platform for forecasting competitions. The platform allows organizations to post their data and have it scrutinized by the world's best statisticians. It will offer a robust rating system, so it's easy to identify those with a proven track record. Organizations can choose either to follow the experts, or to follow the consensus of the crowd — which, according to New Yorker columnist James Surowiecki, is likely to be more accurate than the vast majority of individual predictions. The power of a pool of predictions was demonstrated by the Netflix Prize, a $1m data-prediction competition, which was won by a team of teams that combined 700 models. Kaggle's first competition is underway, and it is accessing the 'wisdom of crowds' to predict the winner of this May's Eurovision Song Contest." Understandably, participation requires registration.