TensorFlow enables developers to quickly and easily get started with deep learning in the cloud. The framework has broad support in the industry and has become a popular choice for deep learning research and application development, particularly in areas such as computer vision, natural language understanding and speech translation. You can get started using TensorFlow on AWS by launching the AWS Deep Learning AMI which comes bundled with TensorFlow; as well as, other popular deep learning frameworks such as Apache MXNet, Caffe, Caffe2, Theano, Torch, Keras, and the Microsoft Cognitive Toolkit.

People who use Box's service to store their digital documents could find it easier to deal with files with lots of pictures. The enterprise software company said Thursday that it's now using Google's (goog) image recognition technology to power a new service. That service is intended to help its customers who need to identify objects in photos and pictures in their online files. Box (box) CEO Aaron Levie said that the service is suited for companies like retail shops that store images of their department store interiors and what to outline every detail in those photos. Before, those companies would have to use people to view each photo and manually label everything in it, like each individual item on a store shelf.

HARI SREENIVASAN: But first: As more and more shopping is done online, what will become of the 16 million Americans who work in the retail industry? Our economics correspondent, Paul Solman, takes a look. It's part of our series Making Sense, which airs Thursdays on the NewsHour. JENNIFER RICHTER, Former Regional Director, Macy's: This is a great, great, great basic black top. PAUL SOLMAN: This summer, Jennifer Richter opened her own clothing boutique online.

The day before a fully automated grocery store opened its doors in 1939, the inventor Clarence Saunders took out a full page advertisement in the Memphis Press-Scimitar warning "old duds" with "cobwebby brains" to keep away. The Keedoozle, with its glass cases of merchandise and high-tech system of circuitry and conveyer belts, was cutting edge for the era and only those "of spirit, of understanding" should dare enter. Inside the gleaming Tennessee store, shoppers inserted a key into a slot below their chosen items, producing a ticker tape list that, when fed into a machine, sent the goods traveling down a conveyer belt and into the hands of the customer. "People could just get what they want – boom, it comes out – and move on," recalled Jim Riot, 75, who visited the store as a child. "It felt like it was The Jetsons." Despite Saunders' best efforts, the Keedoozle's circuits frequently failed and the store closed for good by 1949.

Amazon has a sale on Logitech products today. These are not incredibly deep discounts--despite the savings claims on Amazon's sales page. Nevertheless, there are a few good buys here that are worth pointing out. Amazon's Logitech sale lasts until just before midnight on Tuesday evening. The MX Master Mouse is available for $50 today, which is a savings of about $14 off the previous price. This Bluetooth mouse has a thumb wheel for horizontal navigation.

Jeff Bezos might be the world's biggest Star Trek fan. At one point, the Amazon founder and CEO wanted to call his e-commerce platform makeitso.com, in reference to Captain Jean-Luc Picard's catchphrase. In 2016, after years of begging Paramount Pictures, Bezos made a cameo as an alien Starfleet official in Star Trek Beyond. So, when Amazon set out to build the AI assistant Alexa, Bezos envisioned finally realising the Star Trek computer - a benign, omniscient assistant, available everywhere. "We really did think of it as the Star Trek computer, where it was ambient and you could simply say: 'Computer, beam me up,'" says Mike George, Amazon's vice president of Echo, Alexa and Appstore. Clad in a black v-neck jumper and jeans, the 20-year Amazon veteran has a booming laugh and a vague resemblance to both Bezos and Picard. George bounds into the office, all unwavering eye contact, full-body laughs and wrist-crunching high fives, his preferred form of greeting. I meet him, and most of the Alexa executive team, on an upper floor of Amazon's skyscraper, Day 1, in the Denny Triangle in downtown Seattle. From here, on a blue-sky morning, the Space Needle is dwarfed by the snow-capped mountains beyond. Both seem like inconsequential theatrical set pieces to the Amazon empire below.

It's not about just about the individual jobs that are going away or how fast the rate of new jobs that will be created by Artificial intelligence, it's about entire industries becoming automated in a short-period simultaneously. So which industries are high-risk in the years to come for automation and big-scale human displacement of tasks and jobs? From robot cooks to ordering food home via delivery to automated convenience stores, it's clear the fast-food, convenience stores and the cafe sector will become automated very quickly. This is a deceptively high number of jobs. With the retail apocalypse, we've witnessed the start of a shift.

Over 100 marketing leaders from the most prominent retail brands in the world weighed in on consumer engagement strategies in the 2017 study, "Building Lasting Consumer Relationships in Retail," released by Persado and WBR Digital. The survey was conducted via in-depth interviews with CMOs and other marketing leadership at US- and UK-based major retailers including Best Buy, Marks and Spencer, Williams-Sonoma, Urban Outfitters, and Nordstrom, amongst many others. The survey reveals that despite retailers' efforts to provide relevant content and experiences, they continue to fall short on the personalization front. How these companies are personalizing might be standing in the way of better communication. According to the study, marketers are overly relying on demographic and geographic data, while significantly underutilizing behavioral data, lifecycle stages, and psychographic indicators like emotional triggers.

Recommender systems (RS) help users navigate large sets of items in the search for "interesting" ones. One approach to RS is Collaborative Filtering (CF), which is based on the idea that similar users are interested in similar items. Most model-based approaches to CF seek to train a machine-learning/data-mining model based on sparse data; the model is then used to provide recommendations. While most of the proposed approaches are effective for small-size situations, the combinatorial nature of the problem makes it impractical for medium-to-large instances. In this work we present a novel approach to CF that works by training a Denoising Auto-Encoder (DAE) on corrupted baskets, i.e., baskets from which one or more items have been removed. The DAE is then forced to learn to reconstruct the original basket given its corrupted input. Due to recent advancements in optimization and other technologies for training neural-network models (such as DAE), the proposed method results in a scalable and practical approach to CF. The contribution of this work is twofold: (1) to identify missing items in observed baskets and, thus, directly providing a CF model; and, (2) to construct a generative model of baskets which may be used, for instance, in simulation analysis or as part of a more complex analytical method.

While many studies explore the distant future of AI, this article will focus on the exciting developments that we can see taking place in the online economy right now, and what we can expect to see in the next five years. AI is already changing how our work is done; reinforcing the role of people as drivers of business growth, while also improving efficiency through automation. Let's explore how AI is not only contributing to the growth of the online industry but also how it drastically improves the online shopping experience of customers. Check out a previous article on the economics of augmented reality for more reading on recent tech developments. Before we look at the here and now, let's consider where this path of AI may eventually lead us to.