Recent advancements in artificial intelligence and machine learning have hugely contributed to the growth of Image Recognition and Object Detection in retail. While Image Recognition and Object Detection are used interchangeably, these are two different techniques. Image Recognition is the process of analyzing an input image and predicting its category (also called as a class label) from a set of categories. For instance, consider an automatic store checkout scenario. The user displays an SKU in front of a camera that is powered by an Image Recognition software. The software, when trained on all the SKUs present in the store, can predict the SKU shown by the user as one among all the SKUs.

Time-series forecasting is an important task in both academic and industry, which can be applied to solve many real forecasting problems like stock, water-supply, and sales predictions. In this paper, we study the case of retailers' sales forecasting on Tmall--the world's leading online B2C platform. By analyzing the data, we have two main observations, i.e., sales seasonality after we group different groups of retails and a Tweedie distribution after we transform the sales (target to forecast). Based on our observations, we design two mechanisms for sales forecasting, i.e., seasonality extraction and distribution transformation. First, we adopt Fourier decomposition to automatically extract the seasonalities for different categories of retailers, which can further be used as additional features for any established regression algorithms. Second, we propose to optimize the Tweedie loss of sales after logarithmic transformations. We apply these two mechanisms to classic regression models, i.e., neural network and Gradient Boosting Decision Tree, and the experimental results on Tmall dataset show that both mechanisms can significantly improve the forecasting results.

Most of the retail robots have just enough human qualities to make them appear benign, but not too many to suggest they are replacing humans entirely. "It's like Mary Poppins," said Peter Hancock, a professor at the University of Central Florida, who has studied the history of automation. "A spoonful of sugar makes the robots go down." Perhaps no other retailer is dealing as intensely with the sensitivities around automation as Walmart, the nation's largest private employer, with about 1.5 million workers. The company spent many months working with the firm Bossa Nova and researchers at Carnegie Mellon University to design a shelf-scanning robot that they hope both employees and customers will feel comfortable with.

Might AI help improve customer service for the millions of people who shop on Amazon.com? Amazon intends to find out. In a blog post, the Seattle tech giant revealed that it's testing two AI-based systems to handle incoming shopper inquiries. One fields requests from customers automatically and without human intervention, while the other helps human service agents respond more quickly and easily. "It is difficult to determine what types of conversational models other customer service systems are running, but we are unaware of any announced deployments of end-to-end, neural-network-based dialogue models like ours," wrote Kramer.

Amazon's radical new approach to buying foods and speeding up the checkout process goes the next mile today, with a full-size grocery store here. The Amazon Go Grocery opens Tuesday, with more than four times the space of the original, 7-Eleven-style, on-the-go type stores first opened in 2018. The e-tailer, which also owns Whole Foods, launched the Go stores as a way for local workers to get in and out, with a just basics menu that bypassed essentials like fruit and frozen foods. "We believe'Just walk out' technology," makes shopping a better experience, says Cameron Janes, vice-president of Amazon's physical stores division. He gave USA TODAY a sneak-peek tour of the new concept Monday.

The Canadian artificial intelligence (AI) industry has been growing fast, and the country has been aiming for more through massive AI research. There are signs all over that Canada is already having an AI-driven digital economy as cities are emerging as hubs for AI labs and deep learning research. There is an increase in the number of AI startups in cities such as Montreal, Vancouver, and Toronto, among others. Canada has become a breeding ground for AI innovations. Inc. (NASDAQ: AMZN), Intel Corp (NASDAQ: INTC), and Uber Technologies (NYSE: UBER) have invested significantly in AI research in the country.

The data science revolution has important ethical underpinnings. The authors make a powerful case for the development of AI ethics as a subject in its own right. The Ethical Algorithm shows that apocalyptic predictions of an algorithmized society are far from inevitable. Anyone interested in AI should read and process this essential book.

Deepfake video featuring tech billionaires, Jeff Bezos and Elon Musk is doing rounds of the internet. The video which was shared by YouTube channel The Faking on the video streaming platform has received nearly four thousand likes till now. The video shows Bezos imposed on a body of one of the bulbous-headed alien race the Talosians while Musk plays the human captain Pike. The two are then seen talking about technology and human captivity. The Amazon CEO previously made a cameo appearance in 2016's Star Trek Beyond as the big-headed alien.

Lasse Rouhiainen is a best-selling author and international expert on artificial intelligence, disruptive technologies and digital marketing. Finnish in origin but based in Spain, Lasse focuses his work on investigating how companies and society in general can better adapt to, and benefit from, artificial intelligence. Lasse has given keynote presentations, seminars and workshops in more than 16 countries around the world and holds frequent conferences at several universities internationally. He has also provided training to thousands of students and businesses through online e-learning courses. Lasse has been a speaker at renowned seminars such as Mobile World Capital and TEDx, and has worked with top brands and institutions such as Michelin, Össur and the European Union Intellectual Property Office.

Teikametrics, a leading SaaS provider of AI-powered optimization for brands and sellers on Amazon and Walmart, today announced the completion of a $15 million strategic funding round backed by new and existing investors. The announcement follows Teikametrics' selection as one of Walmart's first exclusive advertising optimization partners, and the addition of Srinivas Guddanti, a 14-year senior Amazon veteran, as its Chief Product Officer. Jump Capital led the round and were joined by follow-on investments from Granite Point Capital, MIT Professor of Econometrics, Jerry Hausman, and the former Head of Growth at Facebook and Uber, Ed Baker. "We're thrilled to lead this new round of capital in Teikametrics," said Michael McMahon, founding partner of Jump Capital. "The Company has grown rapidly, and the success of its proprietary AI technology for Amazon is a strong proof point for a broader ecommerce platform opportunity. The partnership with Walmart is a landmark event and we are excited to fund the expansion of the Teikametrics platform across multiple ecommerce channels."