Gap Inc. has had a hand in financing or acquiring other retail technology companies recently. In August, the retailer acquired Drapr, an e-commerce tech company that provides 3D virtual try-on tools. Over the summer, the company also participated in a funding round for Obé Fitness, a home fitness platform. "We believe artificial intelligence and machine learning will shape the future of our industry. Gap Inc. has experience working with CB4's world-class data scientists, so we understand the impact and the wide applications their science can have across sales, inventory and consumer insights, as well as its potential to unlock value and enhance the customer experience," Sally Gilligan, chief growth transformation officer and head of the Strategic Growth Office at Gap Inc., said in a statement.

Data Science in Retail, let's start understanding the applications of data science in retail sector with an example. The analytics team of Target sat down and figured out how to tell if a customer might be pregnant, even before any announcement was made. By analyzing the purchasing trends of its customers, it turned out they could not only assign a level of likelihood that the customer was pregnant, but could even predict a probable due-date. Target figured out how to data-mine its way into a lady's womb. Using that information, the retail company started to mix in offers sent to those customers to include fetal items along with regular coupons.

Alphabet subsidiary Wing has launched a pilot program that will have its drones fly products from the rooftops of shopping centers. In fact, it has already started the program in its biggest market, Logan, Australia. The subsidiary has teamed up with Australian retail property group, Vicinity Centres, to test the new model at Logan's Grand Plaza, where Wing's drones have been flying orders to customers from businesses directly below their launching pad. Wing has been operating in Logan over the past two years, but up until now, businesses have had to co-locate their products at the company's delivery facility. This is the first time the subsidiary is conducting deliveries from participating merchants' existing location instead.

Amazon.com Inc. had long struggled to make a good video game. Now that it finally has a hit release, the company is predicting a bright future for that business. Games could end up being the largest entertainment category over the long haul, Andy Jassy, the chief executive officer, said Tuesday at a technology conference. It's a bold pronouncement for a company with almost a decade of failures in gaming and one that just renewed its commitment to the movie business in the form of an $8.45 billion acquisition of Metro-Goldwyn-Mayer (MGM). A week ago, Amazon released New World, an online computer game where archers and ax wielders colonize a mythical land.

Wouldn't you like to learn how to program Python 3 without any previous knowledge? No problem - with the help of this beginner's guide, you will be able to understand the basic principles of object-oriented programming around variables, loops and classes in no time. This guidebook covers the basics of Python programming. Real practical examples, graphics and smaller exercises help in parallel with understanding. With the help of this beginner's guidebook, many satisfied readers have already been able to get started and expand their own skills, see for yourself!nderstand.

Retailers, banks, and many other companies collect and analyze information, realizing that data runs the Business. For business development, it is necessary to test hundreds of hypotheses through various methods, and here comes Data Science. Data science applies various big data tools and machine learning (ML), including algorithms and methods of artificial intelligence (AI). The task of ML is to "teach" a program to take appropriate actions based on the huge amount of processed data. Big data is the way of collecting, storing, processing and analyzing information.

SAN FRANCISCO & NEW YORK & TEL AVIV, Israel--(BUSINESS WIRE)--Gap Inc. (NYSE: GPS) has acquired the New York and Tel Aviv based start-up Context-Based 4 Casting Ltd. (CB4) that uses cutting-edge AI and machine learning tools to transform retail operations, increase sales and improve the customer experience through predictive analytics and demand sensing. "We believe artificial intelligence and machine learning will shape the future of our industry. Gap Inc. has experience working with CB4's world-class data scientists, so we understand the impact and the wide applications their science can have across sales, inventory and consumer insights, as well as its potential to unlock value and enhance the customer experience," said Sally Gilligan, Chief Growth Transformation Officer, and head of the Strategic Growth Office at Gap Inc. The deal was brokered by Gap Inc.'s Strategic Growth Office, a unit of the company that seeks out opportunities to fuel growth and accelerate new capabilities across its portfolio of brands. CB4's award-winning technology makes recommendations that support new sales and more satisfied customers.

It might feel as though artificial intelligence has reached a critical mass, but it hasn't. In fact, it's only starting to make an impact in some sectors, including retail. But, according to findings collected by KPMG, retail AI has room to grow -- and a lot of it. And by 2027, AI in retail will balloon to $19.9 billion from around $7.3 billion in predicted spending in 2022, per Meticulous Research. All this, and only half of the retail professionals believe they've scratched the surface of what's possible when the technology meets in-person shopping.

Amazon loves to make up sales, and this week's promotion is all about Epic Daily Deals. In press releases, Amazon said the deals are supposedly "Black Friday–worthy." The vast majority of the deals featured in the sale we've seen so far have been OK discounts on OK gear. If you want true Black Friday pricing, you'll likely need to wait until the end of November to see it on a wide scale. However, this year, holiday shipping deadlines will be tighter than ever, so it's smart to try to get a head-start on holiday shopping if there's something you have your heart set on.

With the increase of order fulfillment options and business objectives taken into consideration in the deciding process, order fulfillment deciding is becoming more and more complex. For example, with the advent of ship from store retailers now have many more fulfillment nodes to consider, and it is now common to take into account many and varied business goals in making fulfillment decisions. With increasing complexity, efficiency of the deciding process can become a real concern. Finding the optimal fulfillment assignments among all possible ones may be too costly to do for every order especially during peak times. In this work, we explore the possibility of exploiting regularity in the fulfillment decision process to reduce the burden on the deciding system. By using data mining we aim to find patterns in past fulfillment decisions that can be used to efficiently predict most likely assignments for future decisions. Essentially, those assignments that can be predicted with high confidence can be used to shortcut, or bypass, the expensive deciding process, or else a set of most likely assignments can be used for shortlisting -- sending a much smaller set of candidates for consideration by the fulfillment deciding system.