Supernovas and Novel Insight: Where Machine Learning is Headed Next


As an astronomer at U.C. Berkeley Josh Bloom faces the problem every stargazer does, you can’t possibly scan the skies and catch everything. “There is so much data, that we just can’t have people looking at all of it,” Bloom says. Enter machine learning as an approximation of human intuition and cognition to aid in research and discovery — not just in astronomy — but also in physics, biology and other sciences. Bloom discusses how he is putting machine learning to work in his academic career, attacking as he puts it “a massive needle-in-the-haystack problem,” and how that experience has led to his own machine learning startup WATCH: 14 minutes