The past year has truly shown manufacturers that they need to transform, and at a much faster rate than previously. AI provides speed by increasing your rate of learning and augmenting employees. But while we've put to rest the argument as to whether AI will be transformational for business, many manufacturers are still trying to figure out how AI will be most useful, and where to start. "The big lie about AI is that AI alone will save you," Colin Parris, Senior Vice President and Chief Technology Officer at GE Digital. "But AI only works when you embed it inside a business process."

Colin Parris has a challenging job. As the vice president of software and analytics research at General Electric, Parris must evaluate new technology and applications that can benefit the manufacturing giant. All of which must work within the framework that GE employs when assessing safety and efficiency known as Humble AI. But even after his own rigorous evaluation and approval process there is no easy way to get buy-in from the rest of the company for new ways of doing business. With huge investments in aviation systems, energy and healthcare, GE is always looking for ways to use technology to improve operations, deliver products faster and better anticipate problems along the way -- all areas where AI can potentially be of use.

You'd think that, with Christmas mere days away, we'd be enjoying the holiday season with mulled wine and family time galore. Instead, its likely most of us are scrambling to finish shopping, wrapping and cooking whatever roast beast our family wants, all while attempting to complete those work projects that just keep popping up. While joyous and wonderful, the holidays can also be anything but namaste. Luckily, you can look no further than your trust friend Alexa to provide some much-needed "me time." This year, digital and creative agency Deutsch NY partnered with their artificial intelligence division, Great Machine, to create a wintry guided meditation that is perfect for the season.

When Jason Nichols joined GE Global Research in 2011, soon after completing postdoctoral work in organic chemistry at the University of California, Berkeley, he anticipated a long career in chemical research. But after four years creating materials and systems to treat industrial wastewater, Nichols moved to the company's machine-learning lab. This year he began working with augmented reality. Part chemist, part data scientist, Nichols is now exactly the type of hybrid employee crucial to the future of a company working to inject artificial intelligence into its machines and industrial processes. Fifteen years ago, GE's machine operators and technicians monitored its aircraft engines, locomotives, and gas turbines by listening to their clanks and whirs and checking their gauges.

When Jason Nichols joined GE Global Research in 2011, soon after completing postdoctoral work in organic chemistry at the University of California, Berkeley, he anticipated a long career in chemical research. But after four years creating materials and systems to treat industrial wastewater, Nichols moved to the company's machine-learning lab. This year he began working with augmented reality. Part chemist, part data scientist, Nichols is now exactly the type of hybrid employee crucial to the future of a company working to inject artificial intelligence into its machines and industrial processes. Fifteen years ago, GE's machine operators and technicians monitored its aircraft engines, locomotives, and gas turbines by listening to their clanks and whirs and checking their gauges.

We are entering the era of talking machines--and it's about more than just asking Amazon's Alexa to turn down the music. General Electric has built a digital assistant into its cloud service for managing power plants, jet engines, locomotives, and the other heavy equipment it builds. Over the internet, an engineer can ask a machine--even one hundreds of miles away--how it's doing and what it needs. Fast Company got an exclusive demonstration of the technology before its debut at GE's Minds Machines conference in San Francisco. Voice controls are built on top of GE's Digital Twin program, which uses sensor readings from machinery to create virtual models in cyberspace.

A visitor to GE's Minds Machines event tries out a Web-connected platform that offers real time operational status updates on wind farm turbines. SAN FRANCISCO -- A man dressed like a utility worker approaches an electrical panel. As he moves to touch the metal box a light blinks. Sensors sewn into his overalls have cut the flow of electricity to the box. He can now work without the risk of electrocution.

A man dressed like a utility worker approaches an electrical panel. As he moves to touch the metal box a light blinks. Sensors sewn into his overalls have cut the flow of electricity to the box. He can now work without the risk of electrocution. "This is just one way technology can help workers do their jobs better and more safely," says Stephane Sireau of GE Digital, whose prototype suit was one of many demos at General Electric's Minds Machines conference, which wrapped up Wednesday. "Our mission is to integrate the worker into a digital industrial context," says Sireau, showing how the suit's sensors also provide vital sign data.

There's a lot of sci-fi-level buzz lately about smart machines and software bots that will use big data and the Internet of things to become autonomous actors, such as to schedule your personal tasks, drive your car or a delivery truck, manage your finances, ensure compliance with and adjust your medical activities, build and perhaps even design cars and smartphones, and of course connect you to the products and services that it decides you should use. But there's another path that gets much less attention: the real world. It too uses AI, analytics, big data, and the Internet of things (aka the industrial Internet in this context), though not in the same manner. Whether you're looking to choose a next-frontier career path or simply understand what's going on in technology, it's important to note the differences. A recent conversation with Colin Parris, the chief scientist at manufacturing giant General Electric, crystalized in my mind the different paths that the combination of machine learning, big data, and IoT are on.

There's a lot of sci-fi-level buzz lately about smart machines and software bots that will use big data and the Internet of things to become autonomous actors, such as to schedule your personal tasks, drive your car or a delivery truck, manage your finances, ensure compliance with and adjust your medical activities, build and perhaps even design cars and smartphones, and of course connect you to the products and services that it decides you should use. But there's another path that gets much less attention: the real world. It too uses AI, analytics, big data, and the Internet of things (aka the industrial Internet in this context), though not in the same manner. Whether you're looking to choose a next-frontier career path or simply understand what's going on in technology, it's important to note the differences. A recent conversation with Colin Parris, the chief scientist at manufacturing giant General Electric, crystalized in my mind the different paths that the combination of machine learning, big data, and IoT are on.