Blockchain computer programs are pretty smart--that's why we call them smart contracts--but they're also pretty weak. If they're going to achieve many of the lofty, world-changing goals that blockchain proponents say they will, like revolutionize health care and the energy industry and give people back control of their personal data online, they're going to need to be run in a whole new way. That's where Dawn Song's new startup, Oasis Labs, comes in. This piece first appeared in our twice-weekly newsletter Chain Letter, which covers the world of blockchain and cryptocurrencies. The cryptocurrency world is overflowing with big claims, but Song is a well-known computer science professor at UC Berkeley and a MacArthur fellow (as well as one of MIT Technology Review's 35 Innovators Under 35 in 2009).
UK Prime Minister Theresa May has announced plans to invest in a "whole new industry around AI in healthcare". Researchers at the University of Southern California have developed a new predictive model for heart disease, which makes use of a smartphone app. Machine-learning techniques are poised to hit the mainstream over the next few years. Machine learning has long been touted as the next big thing for healthcare. With countless startups investing in that promise, applications are emerging across everything from diagnostics to drug discovery.
Dawn Song, a Berkeley computer-science professor and MacArthur fellow, is a fan of cloud computing. She also thinks it needs a major rethink. "The cloud and the internet have fundamentally changed our lives mostly for good," she says. "But they have serious problems with privacy and security--users and companies lose control of their data." Outsourcing data storage and processing over the internet has given companies new flexibility and consumers the power to hail rides, find dates, and socialize from a slab of glass in their pocket.
When David Graham wakes up in the morning, the flat white box that's Velcroed to the wall of his room in Robbie's Place, an assisted living facility in Marlborough, Massachusetts, begins recording his every movement. It knows when he gets out of bed, gets dressed, walks to his window, or goes to the bathroom. It can tell if he's sleeping or has fallen. It does this by using low-power wireless signals to map his gait speed, sleep patterns, location, and even breathing pattern. All that information gets uploaded to the cloud, where machine-learning algorithms find patterns in the thousands of movements he makes every day.