Gary Wolf

December 13, 2015

I talked with Vinod Khosla over the summer about machine learning and the Quantified Self.

Khosla was a founder of Sun Microsystems and is one of Silicon Valley’s most experienced investors in Quantified Self companies. His portfolio includes AliveCor, Ginger.io, Jawbone, Misfit, Narrative, and many other toolmakers that people doing QS projects will recognize. In our conversation, I ask Vinod about the role machine learning can realistically play in QS practices.

Below are links to three papers Vinod mentions in the interview:

Khosla, Vinod. “20-percent doctor included: Speculations & musings of a technology optimist.” (2014).

Beck, Andrew H., Ankur R. Sangoi, Samuel Leung, Robert J. Marinelli, Torsten O. Nielsen, Marc J. van de Vijver, Robert B. West, Matt van de Rijn, and Daphne Koller. “Systematic analysis of breast cancer morphology uncovers stromal features associated with survival.” Science translational medicine 3, no. 108 (2011): 108ra113-108ra113.

Ioannidis, John PA. Why Most Published Research Findings Are False. PLoS Med 2, no. 8 (2005)