Story details

   Live Viewers: 198      Total Pageviews: 510

Artificial Intelligence breakthrough as intuition algorithm beats humans in data test

Big-data analysis consists of searching for buried patterns that have some kind of predictive power. But choosing which "features" of the data to analysis usually requires some human intuition. In this case, though, the researchers tested their first prototype system that analysis big-data against human teams in three data science competitions. The machine managed to finish ahead of a total of 615 human teams.

data nodes

Credit: MIT

MIT may soon be replacing human intuition with algorithms. Scientists have created a new big-data analysis system that outperforms 615 of 906 human teams.

In the three competitions, the Data Science Machine made predictions that were 94, 96, and 87 percent as accurate as the winning submissions, performing better than 615 of the 906 participating teams. ‘We view the Data Science Machine as a natural complement to human intelligence,’ Max Kanter, whose master’s thesis provides the basis for the Data Science Machine, told MIT News.

The system exploits structural relationships inherent in database design; databases typically store different types of data in different tables, indicating the correlations between them using numerical identifiers. The Data Science Machine tracks these correlations, using them as a cue to feature construction.

Video: Elon Musk On AI: 'We're Summoning The Demon'

‘There’s so much data out there to be analyzed. ‘And right now it’s just sitting there not doing anything,’ he said.

‘So maybe we can come up with a solution that will at least get us started on it, at least get us moving.’ The Data Science Machine completed its prediction algorithms at ‘inhuman’ speed, taking between two and 12 hours for each submission.

Human teams worked on their algorithms for months.

More information: "Deep Feature Synthesis: Towards Automating Data Science Endeavors." groups.csail.mit.edu/EVO-DesignOpt/groupWebSite/uploads/Site/DSAA_DSM_2015.pdf

Attached file(s)

Submit a Comment (Logged In Users)

Log in to comment or register here

Don't Miss the Next Big Thing.

Stay Updated with Awesome Science Stuffs.

Close