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It's a bit of an odd article, but my guess is that it's a gloss of a press release, and that kind of writing is par for the course for AI/ML press releases.

Gunnar Carlsson, the researcher mentioned, seems to work mainly on an approach related to manifold learning (roughly, finding lower-dimensional structure in high-dimensional data) that's based on algebraic topology. He co-ran a workshop on that last year at NIPS, one of the main machine-learning conferences: https://sites.google.com/site/nips2012topology/ . He's written some highly cited papers on the subject, though it'd be a bit of a stretch to claim he invented the area, since there have been workshops at least back to 2007, that one organized by a set of French researchers: http://topolearnnips2007.insa-rouen.fr/description.html

I would guess the part about removing the human element from data mining is putting an optimistic PR spin on the basic idea of automatically extracting lower-dimensional structure, which, if it works, should allow for less feature engineering. The emphasis on visualization makes sense in that light, if they're planning to sell it as a no-expertise-necessary system: feed it data and get interpretable-by-non-experts viz as output, with any complexity that would normally require "data scientists" being handled automatically.



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