In this new occasional feature in our blog, AndPlus Innovation Lead Abdul Dremali shares his thoughts on what he’s learning in the Executive Education courses he is taking at MIT’s Sloan School of Management.
A long time ago, in a galaxy far, far away, the inhabitants had access to advanced medical care provided by robots. The Star Wars medical droids had the ability to diagnose and treat their patients with extraordinary knowledge and numerous built-in surgical tools. They had extra added bonus skills in reasoning and communication with their patients—any species from any planet speaking any language. Their bedside manner was, of course, impeccable.
You’ve read a number of articles in this space about different types of machine learning, with a high-level view of how they work and the types of technologies that machine learning will enable in the future. “But,” you’re thinking, “What are some of the ways machine learning is being applied right now, to do useful work outside the laboratory?”
If you buy into the hype, you might believe an army of intelligent robots is on the march RIGHT NOW, coming to TAKE YOUR JOB.
Lately the term "Machine Learning" gets kicked around like a hackysack in a stoners basement. It's becoming a ubiquitous buzzword because it really is exciting technology that's finally making its way into our lives, but a large majority of the buzz is nothing more than lazy marketing. Apple is one of the tech giants that's bringing machine learning into the mainstream in effective and even mindblowing ways.
We’ve all been told that “you can’t teach an old dog new tricks,” but any competent dog trainer will tell you that most old dogs can indeed be taught new tricks, when properly motivated and rewarded. For a real teaching challenge, try teaching a computer to reliably identify a Chesterfield couch (or any couch, for that matter) in a photograph.