MIT SMR Connections is the custom content creation unit within MIT Sloan Management Review. In this Q&A, Michelle K. Lee, vice president of the Amazon Web Services (AWS) Machine Learning Solutions Lab, shares real-world examples of machine learning in action, describes four key implementation challenges, and offers other advice. This conversation has been condensed and edited for clarity, length, and editorial style. Q: Can you provide an overview of how artificial intelligence (AI) and machine learning (ML) are driving digital transformation? Lee: AI and machine learning went from being aspirational technology to mainstream extremely fast.
Smart robots seem to be everywhere. Whether they're performing surgery, trouncing Go champions or generating dreamy artwork, computers programmed to learn on their own are growing more intelligent by the day. Southwestern Law School professor Ryan Abbott believes that computers are even generating patentable subject matter. We just don't know about it, he says, because disclosing it on an application might render the invention unpatentable. "Now that very large companies like IBM, Pfizer and Google are investing heavily in creative computing, it's going to play a much greater role in innovation in the future," he says.