Everywhere we look these days, someone is talking about the potential for artificial intelligence and machines to change the face of healthcare and biotechnology. Certainly, there are the pie-in-the-sky ideas about replacing human doctors with robots. But on the more realistic level, we are using the technology to rapidly sift through the vast amounts of genetic information we’ve collected to find associations and links between genetic mutations and various diseases, disorders and health risks.
“Certainly AI is one of the biggest buzzwords that’s around today,” said Gabe Musso, chief scientific officer at BioSymetrics. “But often times, when people are talking about artificial intelligence, what they are really talking about is machine learning. Machine learning is a process that’s been around for a very long time. It’s basically pattern identification. When we get into AI, it’s about how we can make the process autonomous.”
In this episode of Talking Biotech, Musso joins plant geneticist and host Kevin Folta to talk about artificial intelligence and machine learning and how emerging technologies can be used to examine complex data sets in the quest to find patterns that can give us new perspectives in biology. Musso takes these complex concepts and makes them understandable, while describing ways they may be applied in contemporary contexts.
Gabe Musso is the chief scientific officer at BioSymetrics. Follow him on Twitter @gabe_musso
Kevin M. Folta is a professor in the Horticultural Sciences Department at the University of Florida. Follow professor Folta on Twitter @kevinfolta and email your questions to [email protected]
The Talking Biotech podcast, produced by Kevin Folta, is available for listening or subscription:
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