Big Data Analytics: MIT Algorithm to Simulate Human Intuition

Data Science Machine - MIT News
Big Data Analytics: MIT Algorithm to Simulate Human Intuition

MIT researchers claim to have formulated an algorithm that can surpass most humans on tasks that require intuition. The algorithm was designed by a MIT student Max Kanter, as part of his master's thesis at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL)

Named "Data Science Machine" by Max Kanter, the algorithm has beaten 615 out of the 906 human teams it's come up against in a competition, according to Kanter.

Max Kanter entered his  Data Science Machine into three competitions and came on top. While it  didn't garner the top score in any of its three competitions, it created models that were  around 95%  as accurate as those of the winning teams in two and 87 percent as accurate in the third. 

The algorithm is mostly suitable for Big Data Analytics, where human intuition is very important when searching for buried patterns with predictive power.

We view the Data Science Machine as a natural complement to human intelligence. There’s so much data out there to be analyzed. And right now it’s just sitting there not doing anything. So maybe we can come up with a solution that will at least get us started on it, at least get us moving,”  Kanter told Larry Hardesty of MIT News.


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