Santanu Pattanayak works as a Staff Machine Learning Specialist at Qualcomm Corp R&D and is an author of the deep learning book Pro Deep Learning with TensorFlow - A Mathematical Approach to Advanced Artificial Intelligence in Python. He has around 12 years of work experience and has worked at GE, Capgemini, and IBM before joining Qualcomm. He graduated with a degree in electrical engineering from Jadavpur University, Kolkata and is an avid math enthusiast. Santanu is currently pursuing a master's degree in data science from Indian Institute of Technology (IIT), Hyderabad. He also participates in Kaggle competitions in his spare time where he ranks in top 500.

Christmas is just over a week away, which means the holiday shopping season is in full swing. Consumers are spending billions of dollars per day on gifts in anticipation of the big day. But the fraudsters are also out in force to steal a piece of the action. Luckily, AI and machine learning are getting better at identifying these grinches before they ruin things for the rest of us. The math is pretty simple: The bigger the holiday buying season, the bigger the pay day for fraudsters.

Every year before Christmas, consumers face similar dilemmas: what gifts to buy for their loved ones? Selection based on your own tastes can end in failure and returns of gifts. When trying to predict what their loved ones want to find under the Christmas tree, people now more often use new technologies, notes Dr. Artur Modliński from the Department of Management of the University of Lodz. These technologies are applications - artificial intelligence that predicts the hottest holiday trends with advanced algorithms. At the same time, shopping websites often use artificial intelligence to track the behaviour of Internet users; they observe what products they search for, what they most often click, what topics and categories they search for - and what they buy. "This artificial intelligence simply checks and learns how we act and what we are interested in" - he says.

AI and ML are among the top technology trends in the retail world. They have a significant impact on the retail industry, especially in e-commerce firms that rely on online sales. FREMONT, CA: The retail industry is being disrupted and is permanently transforming by the ever-increasing abilities and applications of artificial intelligence (AI) and machine learning (ML). The retail sector has just begun to see the benefits of AI and ML implementations in the retail industry. They have helped forward-thinking companies shorten time to market, enhance margins, and better align their offerings with customers' preferences and expectations.

Technology giants are increasingly designing their own semiconductors to optimize everything from artificial intelligence tasks to server performance and mobile battery life. Google has the Tensor Processing Unit, Apple Inc. has the A13 Bionic and Amazon.com What the titans all lack, however, is a factory to build the new chips they are dreaming up. Enter Samsung Electronics Co., which is planning a decade-long, $116 billion push for their business. The South Korean company is investing heavily in the next step in miniaturizing semiconductors, a process called extreme ultraviolet lithography (EUV).

The ScaleFactor State of SMB Finance report says only 10% of retail businesses are using Artificial Intelligence (AI). The report reveals Small and Medium Business (SMB) retailers are the most reluctant to implement AI or machine learning (ML) solutions into their workflow. Furthermore, 40% say they are not interested in this technology. Despite the disinterest, 44% of retail businesses say they do not find the process of implementing AI or ML challenging; the highest across all industries. And over a third (39%) admit to not knowing AI/machine learning were options for their accounting solutions.

On our sidewalks, in our skies, in our every store… Over the next decade, robots will enter the mainstream of retail. As countless robots work behind the scenes to stock shelves, serve customers, and deliver products to our doorstep, the speed of retail will accelerate. These changes are already underway. In this blog, we'll elaborate on how robots are entering the retail ecosystem. On August 3rd, 2016, Domino's Pizza introduced the Domino's Robotic Unit, or "DRU" for short.

Google Cloud VP of Retail Carrie Tharp has a long background of embracing disruption. Having joined the Mountain View, Calif.-based tech giant in July, she might be a relative newcomer, but she is no stranger to developing and supporting technology for the changing retail landscape. Tharp spent the past three years at Neiman Marcus Group creating the luxury retailer's digital-first strategy, including shifting to a cloud-centric software stack for marketing and ecommerce and leveraging artificial intelligence and machine learning to drive programs like digital styling, personalized promos and algorithmic buying. Before that, she was immersed in similar tasks at Fossil and Travelocity. One theme that weaves throughout her career: Tharp embraces the challenge of shepherding retail brands through disruption and helping them evolve the way they interact with customers.

The Amazon reviews of course don't count, at least 10 out of 11 are clearly written by neophytes. I heard the book is quite critical of current trends in AI research, which might be good if the critique is well-articulated. But I also heard the book criticizes the ImageNet dataset, which was fundamental for ML progress in Computer Vision and beyond, so I'm skeptical. I don't know much about the author's research: doesn't seem to have published much in conferences such as NeurIPS, ICLR, ICML, etc. so I'm not sure about her qualifications as an expert on the subfield of AI she decides to talk about. On the other hand, apparently both Anima Anandkumar and Thomas Dietterich had good words for the book, and they're definitely experts in the field.

The year 2019 seemed to be the year of unpredictability, not the least of which was the seemingly ever-changing foreign trade policy of major world economies. Interestingly, it's that same unpredictable nature of foreign trade policy that serves as a springboard for supply chain predictions for 2020. Here are the top five predictions that will have a major impact on the world's global supply chains. Historically, digital transformation of the supply chain has taken place by targeting various functional silos within their own walls. This approach lacked the ability to evaluate the interconnected nature of supply chain decisions.