Commerce moved beyond brick-and-mortar stores, seized the online space, and is steadily crippling into mobile. Modern online shopping offers unparalleled flexibility of access and selection of available interfaces. You can shop away while on a bus. You can buy your next favorite gadget while relaxing on a lawn on a beautiful sunny day. That's why mobile commerce is such a fast-growing niche that caters specifically to smartphone users and their respective app ecosystems.

Booksby.ai is an online bookstore which sells science fiction novels generated by an artificial intelligence. Through training, the artificial intelligence has been exposed to a large number of science fiction books and has learned to generate new ones that mimic the language, style and visual appearance of the books it has read. None of the stories, titles, descriptions, book covers or reviews related to any of the books on Booksby.ai has been written or designed by humans. All books on Booksby.ai are for sale on Amazon.com and can be ordered as printed paperbacks. The stories, titles, description and reviews of the books were generated using char-rnn-tensorflow and training data from Amazon.com and Project Gutenberg.

The benefits of artificial intelligence technology, specifically around merchandise management, is clear to most retailers but just 16% have deployed an AI engine, according to a study from Symphony RetailAI and RIS News. The study identifies top challenges retailers face with merchandising planning and their perception of AI, according to a press release. It also lists three specific applications retailers view as critical for meeting merchandise management goals: demand forecasting (56%), replenishment (44%) and price management (41%). Retailers are most excited about AI's support in reducing out-of-stocks (56%) and over-stocks (34%), creating real-time inventory visibility (41%) and improving inventory accuracy (34%), according to the release. "As retail becomes more intelligent and consumer preferences become more fluid, the study's findings make it clear that now is the time to invest in AI to improve merchandise management outcomes," said Kevin Sterneckert, CMO, Symphony RetailAI, in the release.

Financial institutions that extend credit face the dual tasks of evaluating the credit risk associated with each loan application and determining a threshold that defines the level of risk they are willing to take on. The evaluation of credit risk is a common application of machine learning (ML) classification models. The determination of a classification threshold, though, is often treated as a secondary concern and set in an ad hoc, unprincipled manner. As a result, institutions may be creating underperforming portfolios and leaving risk-adjusted return on the table. In this blog post, we describe how to use Amazon SageMaker automatic model tuning to determine the classification threshold that maximizes the portfolio value of a lender choosing a subset of borrowers to lend to. More generally, we describe a method of choosing an optimal threshold, or set of thresholds, in a classification setting. The method we describe doesn't rely on rules of thumb or generic metrics. It is a systematic and principled method that relies on a business success metric specific to the problem at hand. The method is based upon utility theory and the idea that a rational individual makes decisions so as to maximize her expected utility, or subjective value. In this post, we assume that the lender is attempting to maximize the expected dollar value of her portfolio by choosing a classification threshold that divides loan applications into two groups: those she accepts and lends to, and those she rejects. In other words, the lender is searching over the space of potential threshold values to find the threshold that results in the highest value for the function that describes her portfolio value.

The artificial intelligence industry has skyrocketed in recent years, powering technologies behind smart speakers and self-driving cars, but that growth is coming at a cost. Researchers at the University of Massachusetts Amherst recently conducted a study assessing the energy consumption required to train several common large AI models. The study revealed that the training process can emit over 626,000 pounds of carbon dioxide, nearly 5x the lifetime emissions of an average car, or the equivalent of about 300 round-trip flights between New York and San Francisco. The benefits from the advancements in AI and other emerging technologies at the expense of the environment are simply not worth it, say many industry experts who are urging big tech companies to ramp up their sustainability efforts. Failing to do so could leave the companies' reputations at risk, they said.

Artificial Intelligence is the hottest and most promising development in the tech landscape for a couple of years, now. According to market firm Tractica, global AI revenues will see a massive growth from just USD 643.7 million in 2016 to an excess of USD 36.8 billion in 2025. Nearly all the market segments, industries, and business domains are actively interested in AI and are looking to harness the technology for business benefits. AI offers companies the power to reduce costs and make the shopping experience much more delightful and efficient for the end consumers. According to Global Market Insights, investments in AI by retail segment will exceed USD 8 billion by 2024.

Today's Buzz: "As the concept of "New Retail" spreads globally, many Fortune Global 500 retail companies are implementing AI technologies such as computer vision and NLP in unmanned stores and warehouses or virtual stores and are accelerating supply chain upgrades to better position themselves for the future of shopping" (medium.com). "Retailers often feel understandably reluctant to give emerging technologies a try unless they feel extremely confident in the eventual payoff. A Capgemini Research Institute study…showed that if retailers branched out and deployed AI across their operations, they could save more than $340 billion by 2022" (www.mytotalretail.com). We'll ask four experts for their take: Brian Kilcourse, Retail Systems Research; Praful Karanth, SAP; Matt Laukaitis, SAP; Roger Roney, SAP. Join us for "Truth or Dare: Is AI the Future of Retail?"

The benefits of artificial intelligence technology, specifically around merchandise management, is clear to most retailers but just 16% have deployed an AI engine, according to a study from Symphony RetailAI and RIS News. The study identifies top challenges retailers face with merchandising planning and their perception of AI, according to a press release. It also lists three specific applications retailers view as critical for meeting merchandise management goals: demand forecasting (56%), replenishment (44%) and price management (41%). Retailers are most excited about AI's support in reducing out-of-stocks (56%) and over-stocks (34%), creating real-time inventory visibility (41%) and improving inventory accuracy (34%), according to the release. "As retail becomes more intelligent and consumer preferences become more fluid, the study's findings make it clear that now is the time to invest in AI to improve merchandise management outcomes," said Kevin Sterneckert, CMO, Symphony RetailAI, in the release.

Through the power of AI, Adobe has today predicted online shopping during the 2019 holiday season (Nov. 1 through Dec. 31) to reach $143.7bn. And according to the research, powered by Adobe Sensei, Adobe's AI and machine learning technology, advertisements will play a significant role in where these dollars are spent. Fifty per cent of consumers state that ads during the holiday shopping season impact their purchasing decisions while email continues to be the most preferred way to get an offer while holiday shopping. Smartphone visits to retail sites from social media have tripled in the past three years from four per cent to 11 per cent. However, visits coming from social platforms result in lower conversions compared to other channels like search or email.

Artificial Intelligence in retail market is expected to grow at CAGR of 38.5% during the forecast period, 2019–2026. AI has become a cardinal element across various industry verticals for digitalization, especially in the retail segment. According to the World Economic Forum, e-commerce is on the verge of becoming the most important retail channel, driving 42% of consumption growth and 90% of the growth from mobile e-commerce. Thus, implementing advanced technologies in e-commerce, such as artificial intelligence, would offer better prospects for the retail industry in the coming years. AI is predicted to unleash a digital disruption in retail with prominent industry players ramping-up their businesses. AI-powered solutions are increasingly becoming a priority for the food & beverage industry and retailers.