Sparse alpha-norm regularization has many data-rich applications in Marketing and Economics. Alpha-norm, in contrast to lasso and ridge regularization, jumps to a sparse solution. This feature is attractive for ultra high-dimensional problems that occur in demand estimation and forecasting. The alpha-norm objective is nonconvex and requires coordinate descent and proximal operators to find the sparse solution. We study a typical marketing demand forecasting problem, grocery store sales for salty snacks, that has many dummy variables as controls. The key predictors of demand include price, equivalized volume, promotion, flavor, scent, and brand effects. By comparing with many commonly used machine learning methods, alpha-norm regularization achieves its goal of providing accurate out-of-sample estimates for the promotion lift effects. Finally, we conclude with directions for future research.

What will AI's role be during this busiest of all seasons? The holiday season means many things to many people; to retailers and e-tailers, it means things are about to get crazy busy. This is true no matter when the shopping season begins. In the US for example, it traditionally stretches from Thanksgiving to just after the New Year; in India, it runs from mid-August to January. Retailers of all sorts are already adapting their approach by timing sales and tying them into holidays or other festive events.

So it's been an interesting first few weeks with the Echo and am happy to say Echo 2nd Gen has finally delivered on its promise of improved sound quality over 1st Gen Echo, with the 3rd firmware since launch. If you are confused about a lot of the negative reviews, old firmware is the likely cause of most of them regarding poor sound quality. Want to keep this short and spare all the gory details, but there was a bug in the launch version of the firmware, which was fixed after a few days, but the first fix, while satisfying some, was not, in my opinion a full fix and left the mid-range frequencies muted and tinny. Today I noticed that Alexa's voice in this unit sounded much more like Alexa's voice on Gen 1 Echo's I own and, after playing some music, suspected they had upgraded the firmware again, and indeed they have. The current firmware is 592452720 and it's a massive improvement over both the original and updated version 592452420.

Walmart may be grabbing headlines for its embrace of cutting-edge technologies, but at the heart of those changes are companies like Bossa Nova. The San Francisco-based robotics firm created the robots now roaming the aisles in 50 Walmart locations around the US. Bossa Nova's robots are able to perform tasks such as identifying when items are out of stock, locating incorrect prices, and detecting wrong or missing labels. We spoke to Martin Hitch, chief business officer at Bossa Nova, about the technology behind the machines and how they are being received by shoppers and employees. This article is part of a weekly series paired with our newsletter Clocking In, which covers the impact of technology on the future of work.

Global retail spending on artificial intelligence will grow to $7.3 billion per year by 2022, up from an estimated $2 billion in 2018, according a study from Juniper Research. In coming years, retailers will spend heavily on AI tools that will enable them to differentiate and improve the services they offer customers. These will include automated marketing platforms that generate tailored, timely offers, and chatbots that provide instant customer service. Retailers are planning to spend more on AI, with customer service and sentiment analytics receiving the most attention, Juniper found in its most recent research. A key tool for retailers seeking to improve their customer experience will be applying AI to understand customer reaction to the products purchased and the service received.

Many workers are anxious about the integration of robots into the workforce because of the potential job losses for people, particularly in low-skilled sectors. But in 50 Walmart locations around the United States, robots from the San Francisco-based robotics firm Bossa Nova are welcomed with open arms. These robots are taking on some of the most tedious tasks: identifying when items are out of stock, finding incorrect prices and missing or incorrect labels. And, according to Martin Hitch, chief business officer at Bossa Nova, who spoke with MIT Technology Review, employees love the bots and surprisingly customers don't seem to care. Hitch explained that one of the ways that seemed to help the robots "fit in" and be quickly accepted by the staff was that they gave them a name.

This article originally appeared in the Motley Fool. Artificial intelligence (AI) is getting a lot of attention from investors these days and with good reason. It's a technology with the potential to transform everything from transportation to cloud computing. Many companies are betting that AI will influence not just their products and services, but nearly every aspect of their business. Read on to discover nine things you may not have to know about this burgeoning technology. Artificial intelligence is often used as a catch-all to describe computer systems that can learn.

Technology expectations and economic statistics are clashing for now -- but the reality is more promising than it appears. We see the effects of transformative new technologies everywhere except in productivity statistics. Systems using artificial intelligence (AI) increasingly match or surpass human-level performance, driving great expectations and soaring stock prices. Yet measured productivity growth has declined by half over the past decade, and real income has stagnated since the late 1990s for a majority of Americans. What can explain this paradox?

So why is this relevant to retail and how can it improve in-store sales? Retailers can now predict buying behavior with a greater degree of accuracy by understanding what products their shoppers are engaging with and how, whether they are trying on a product or simply picking it up. Machine learning principles can identify human actions of both shoppers and employees, including crouching, bending, reaching overhead, and the like, all the way down to analyzing what aids are being used – carts, bags, brooms, mops, and more.

I got completely lost in this book as hurricane Irma roared around my house in Miami. No really, it is that good. From start to finish the work is thought provoking, completely engrossing and yet fun and easy to read. The groupings of the stories into six sections (Aliens and Alien Worlds, Artificial Intelligences, Silo Stories, Fantasy, Algorithms of Love and Hate, Virtual Worlds, and Lost and Found) gives you an indication that this book covers and incredibly wide range of topics. So much of this is new ground and when Howey delves into trope themes (like alien invasions) the stories are completely fresh.