This is Bloomberg Opinion Today, an updated Bayeux Tapestry of Bloomberg Opinion's opinions. Apple Inc. recently added audiobook narration to the growing list of occupations where algorithms are poised to replace humans alongside graphic designers, college essayists and limerick writers. Luckily, the fine art of newslettering remains (ahem) far beyond the capabilities of even the most sophisticated artificial intelligence software. Still, hope is at hand for those not fortunate enough to toil in the newsletter mines but still seeking gainful employment that won't disappear as robots take control.

In the meantime, if one of them goes berserk, here's a useful tactic: Shut the door behind you. One after another, robots in a government-sponsored contest were stumped by an unlocked door that blocked their path at an outdoor obstacle course. One bipedal machine managed to wrap a claw around the door handle and open it but was flummoxed by a breeze that kept blowing the door shut before it could pass through. Robots excel at many tasks, as long as they don't involve too much hand-eye coordination or common sense. Like some gifted children, they can perform impressive feats of mental arithmetic but are profoundly klutzy on the playground.

JUDY WOODRUFF: The idea, how technology, music and science can inspire one another, and to the creation of distinct new sounds. Jeffrey Brown is back to take us to an unusual gathering held just a few days ago in Durham, North Carolina. JEFFREY BROWN: Start with a circuit board, add knobs and dials, solder everything together, and, eventually, if you know what you're doing, you have an instrument that can do this. Moogfest, named after inventor Robert Moog, is a celebration of the art, engineering and technology of synthesizers, machines that create sounds electronically. By night, it's a festival of different genres of music, centered on, as they call them here, synths.

What if machines could learn? This has been one of the most intriguing questions in science fiction and philosophy since the advent of machines. With modern technology such questions are no longer bound to creative conjecture, machine learning is all around us. From deciding which movie you might want to watch next on Netflix to predicting stock market trends, machine learning has a profound impact on how data is understood in the modern era. This tutorial aims to give an accessible introduction to how to use machine learning techniques for your own projects and datasets.

The consumer in-store retail experience is undergoing a critical evolution, and it's clearly upended the retail industry: in the first four months of 2017 alone, there have been fourteen retail bankruptcies -- almost as many as in all of 2016. Other companies, such as J.C. Penney, Macy's, and Sears, have announced massive store closures. While putting together Firebrand Group's Future of Artificial Intelligence report for our clients (you can get an excerpt, focused on retail innovation, here), my team and I reviewed nearly one hundred brands engaging in some form of retail innovation. Starbucks already allows people to order remotely and go into their retail locations to pick up drinks, and is presently deploying an AI assistant into their app. Called My Starbucks Barista, the feature will allow users to place orders with one tap of a button, then speaking to a virtual barista.

Movies and television have proved to be uncanny indicators of what's to come. Innovations that first appeared in 2001: A Space Odyssey and The Minority Report and even Star Trek and The Jetsons, are now fully integrated into how we work and play. But how much is too much? And are businesses equipped to handle these disruptions that have turned the traditional customer journey on its head? These topics and more were discussed during a thought-provoking keynote presentation called "The Sci-Fi Future of Customer Engagement" delivered by Jamie Anderson, Chief Marketing Officer for SAP Hybris.

We've all heard the alarms sounding over the last few years -- the trifecta of robots, automation and artificial intelligence are marching in lockstep, shiny arms raised, taking not just our factory and mechanical jobs but also our mid-to-high level white collar jobs in finance, marketing and, ahem, journalism. A new survey by Pew Research Center called "The Future of Jobs and Jobs Training" follows a slew of studies, panels, FAQs and articles which herald this disconcerting prospect. But the report offers some hope: with the proper approach to training, learning and education, humans will do just fine in this brave new world. There's a catch: you have to reimagine everything you think you know about training, learning and education. Focusing on learning specific skills such as a particular computer programming language will not be the answer, Lee Rainie, a co-author of the Pew report, told CMSWire.

Neural networks are a rapidly developing paradigm for information processing based loosely on how neurons in the brain processes information. A neural network consists of multiple layers of node, where each node performs a unit of computation, and passes the result onto the next node. Multiple nodes can pass inputs to a single node, and vice-versa. The neural network also contains a set of weights, which can be refined over time as the network learns from sample data. The weights are used to describe and refine the connection strengths between nodes.

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