• Anil Babbar

Intelligent Application of A.I.

Years ago, whenever I thought of Artificial Intelligence (A.I.) I would conjure up sci-fi based stories of an evil computer system (HAL 9000 / Skynet) or a Terminator bent on destroying mankind with the perceived cold logic of a silicon chip. TV shows and movies such as Star Trek, Blade Runner, Spielberg's A.I. and Ex-Machina anthropomorphized the A.I. by making it sentient and seeking human emotions such as love and the desire to live (see the “Offspring” ST TNG S03E16). This is great sci-fi entertainment that prods the viewer to explore "deep thoughts" on the potential impact of A.I. on our rights (and the rights of a sentient A.I?), our economy and society.

Now for reality. ASA Capital's investment in BUDDI AI (Claritrics Inc.) - an A.I. deep learning platform solving healthcare auto-coding and revenue cycle management) has given me some insight on how difficult it is to apply A.I. in the real world for a meaningful result. Throwing "Big Data" at a machine does not solve anything. There is no magical output. The data must have a certain logical format - structure. It has to be cleaned (useless noise removed), curated (ensure meaningful facts are present), and then fed to an A.I. to extract knowledge and insights hidden in its history and present interactions - with a contextual understanding. This is where the deep learning happens.

A fundamental understanding of the workflows, the exceptions, and challenges of an industry are required to allow for modifications driven by HUMAN intelligence that feeds and hones what the machine learns. BUDDI AI is getting this done in the right way.

See: “Jefferies gives IBM Watson a Wall Street reality check

Tags:

A.I.

Machine Learning

Healthcare

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