After analyzing data from over a quarter million patients, the neural network can predict the patient’s age (within a 4-year range), gender, smoking status, blood pressure, body mass index, and risk of cardiovascular disease.
The implications are far less humorous, however. Prepare for #FakeNews 2.0.
You don’t need to change the world for deep learning to have a meaningful impact in your life.
The word on every tech executive’s mouth today is data. Curse or blessing, there’s so much data lying around – with about 2.5 quintillion bytes of data added each day – that it’s become increasingly difficult to make sense of it in a meaningful way. There’s a solution to the big data problem, though: machine learning algorithms that get fed countless variables and spot patterns otherwise oblivious to humans. Researchers have already made use of machine learning to solve challenges in medicine, cosmology and, most recently, crime. Tech giant Hitachi, for instance, developed a machine learning interface reminiscent of Philip K. Dick’s Minority Report which can predict when, where and possibly who might commit a crime before it happens.
Using a novel deep learning algorithm, a team at UC Berkeley demonstrated a robot that learns on the fly and performs various tasks that weren’t pre-programmed. It starts off shy and clumsy, but eventually gets the ahead of it. For instance, after it stomped a bit around its environment, when given a new task, but with no further instructions, the robot learned by itself to assemble LEGO bricks or twist caps onto pill bottles.