Chatbots have been around for a while. Yet, now that Facebook will allow businesses to deliver automated customer support and interactive experiences through bots, they will be everywhere soon. Brands might feel that they should replace their human employees with chatbots now, but they should think hard before shaking up the status quo. Ideally, humans and chatbots will work together to do the tasks they are best equipped to handle in order for both parties to be most effective. While bots are being touted by some as the next big thing for handling customer service needs, chatbots are not sufficiently equipped to serve as the complete answer to a brand's growing requirements.

How an ecommerce company used predictive analytics to improve customer retention. Acquiring new customers is much more expensive than retaining current ones. Keeping customers from unsubscribing from a company's services or from choosing another company's solution is therefore a challenge that should be at the top of every corporate agenda. A way to address this challenge is through predictive customer churn prevention, in which data is used to find out which customers are likely to churn in order to win them back -- before they are gone. Showroomprivé.com, an ecommerce company founded in 2006, sought ways to employ machine learning approaches to retain more customers.

TECHNOLOGY-FUELED INNOVATION IS NOT AN ANOMALY, BUT RATHER A NEW REALITY. The ability of a company to both foresee and manage fast change increasingly dictates success in the marketplace and CART is seeing a growing number of retailers, wholesalers, and brand manufacturers diving into emerging technologies. The increasing pace of technology-fueled innovation is not an anomaly, but rather a new reality. With more than 45,000 users, the CART platform provides powerful insight into what technologies and innovation the retail industry is focused on. The second quarter of 2016 has seen a growing number of retail industry executives realize that the frenzy of technology-fueled innovation is not an anomaly, but rather a new reality.

Tiro Partners is representing a major high street and online retailer in central London who are looking to build out a Recommender based system and a Forecasting System. The successful engineer must have a deep understanding of the algorithms used and why they are apprpriate. He/she must also be familiar with Workflow definition, Model Taining and Data Regularisation. Communication and mentoring skills are also essential; will be expected to explain what is being done and interact with a team of very talented but inexperienced engineers in the Machine Learning field. The initial work will focus on building the recommendations engine that will be use in the eCommerce site.

I have to admit that when "Big Data" starting getting a lot of traction, I was not a fan of the phrase as I often work with organisations who do not think of themselves in terms of having a lot of data. We can talk all we want about the multiple dimensions of big data, commonly referred do as the "V's" (volume, variety, velocity and veracity) but what sticks is the term "Big Data" and that conjures up images for people, after all marketing is powerful tool! Even today, I often have discussions regarding how a specific customer can take advantage of the new capabilities introduced in the era of big data, regardless of the size of the data stored. There are many different genres of analytics available that can be utilised to extend your analytic capabilities. Three of the most common include graph analysis, path analysis and text analysis.

Digital Mind Math is a complete mathematical model of the mind and cognition-a model for the sciences of artificial intelligence, neuroscience, and cognitive psychology, and also of interest to anyone who thinks and anyone who enjoys having a mind. The two critical components of the Digital Mind Math model are p-adic mathematics and reconfigured spacetime, both of which are central to the theory of physics Topological Geometrodynamics (TGD) that Digital Mind Math is based on. New Physics and the Mind In Digital Mind Math, details are grouped to form concepts, as the mind identifies the boundaries of thoughts, which are intricately linked in real spacetime. The contents, sequences, and interconnections among thoughts are efficiently labeled using p-adic mathematics. P-adic mathematics-the mathematics of enclosure and sequencing-is our first mathematics, how we organize our world from infancy onward, the natural mathematics of cognition.

Security robots at a shopping centre in Silicon Valley have been taken off duty after one of them ran over a toddler. His mother told ABC News the robot had hit her son's head, "he fell down on the floor, and the robot did not stop". The 16-month-old, Harwin Cheng, was left with swelling to his right foot. The robot's developer, Californian start-up Knightscope, apologised for the "freakish accident" and invited the family to visit its Mountain View headquarters. It said: "A child... began running towards the machine. "The machine veered to the left to avoid the child, but the child ran backwards directly into the front quarter of the machine, at which point the machine stopped and the child fell on the ground.

The security robots are made by a company called Knightscope, located in Mountain View. The K5 version uses lasers, thermal imaging sensors, 360 video, air quality sensors, a microphone and various other technologies to deter and detect criminal activities. In the event of suspicious activity, the robot alerts local human authorities. Stacy Dean Stephens, Knightscope vice president of marketing and sales, told NBC Bay Area that the company does not think the robots are dangerous. "This is a horrific accident, but we believe the technology and the machines are incredibly safe and we will continue to do our best to make sure that they are," Stephens said.

Someone at Google really likes sneakers: The company has just bought a French machine learning startup that taught a computer how to recognize 15,000 different types of them. Paris-based Moodstocks builds image and object recognition software using deep learning techniques, and offered an Android app and visual search API that could recognize certain kinds of object. By analyzing video from a smartphone camera, and correlating it with accelerometer readings to determine how the camera is moving around, the software is able to infer information about the three-dimensional shape of objects in the video, facilitating their recognition. In February 2015 the company demonstrated its ability to identify sneakers through its app. Three months later, after training the software using 15,000 photos of shoes from an online retailer's website, Moodstocks claimed to be able to shop online for all the sneakers on sale in a Macy's store. Google has been introducing elements of machine learning into its existing online services, including Google Translate and Inbox, a next-generation interface for Gmail.

No brand in retail generates more questions, opinions and fascination than Amazon. So each year the Internet Retailer Conference Exposition hosts Amazon & Me, a day-long pre-conference workshop designed for retailers and branded manufacturers alike. Described by moderator/organizer Scot Wingo as "a curated mix of Amazon strategies and tactics that both beginners and advanced as well as retailers and brands can utilize," Amazon & Me 2016, held earlier this week, drilled deep into the Amazon mystique in an effort to better understand the company's business model, its core philosophies and its ultimate goals. Here are five major takeaways from this year's event. According to Wingo, the co-founder and executive chairman of e-commerce solutions provider ChannelAdvisor, Amazon's revenues are growing 26% year over year, and it now serves 310 million active buyers, a customer segment increasing 13% annually.