Before the coronavirus hit, consumer expectations were already changing and creating challenges in the retail industry. And CIOs, who historically had little to do with developing new customer experiences, were increasingly being tasked with driving innovation. To deliver Amazon-like here-and-now products and services and build brand loyalty, they are turning to artificial intelligence (AI) to improve the shopping experience for consumers both in stores and online. Of course, AI alone won't transform retail but there are several key technologies that when married with AI can bring innovation to that industry. One is video analytics, which turns regular stores into intelligent stores that have visibility into consumer behavior for optimized merchandising.

Retailers looking to develop new customer experiences need to make artificial intelligence part of their digital transformation plans or risk falling further behind. Before the coronavirus hit, consumer expectations were already changing and creating challenges in the retail industry. And CIOs, who historically had little to do with developing new customer experiences, were increasingly being tasked with driving innovation. To deliver Amazon-like here-and-now products and services and build brand loyalty, they are turning to artificial intelligence (AI) to improve the shopping experience for consumers both in stores and online. Of course, AI alone won't transform retail but there are several key technologies that when married with AI can bring innovation to that industry.

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The coronavirus pandemic is changing the way we shop, especially for groceries. From donning masks to wearing gloves, many Americans are taking extra precautions when stocking up on pantry staples and other essential items. Grocery shopping online has become a great option for many during quarantine, and if you're shopping at Walmart, Google Assistant can help. With a few simple voice commands, you can order everything you need from Walmart using a Google-Assistant-enabled speaker or smartphone. While this may not be ideal for massive shopping lists, when you're standing in your kitchen looking at a cookbook or recipe site, it's convenient to just read off what you need to your smart assistant.

At supermarkets like Giant Eagle, robots are freeing up employees who previously spent time taking inventory to focus on disinfecting and sanitizing surfaces and processing deliveries to keep shelves stocked. Retailers insist the robots are augmenting the work of employees, not replacing them. But as the panic buying ebbs and sales decline in the recession that is expected to follow, companies that reassigned workers during the crisis may no longer have a need for them. The role of a cashier is also changing. For many years, retailers have provided self-checkout kiosks.

Metals shop and auto mechanics in high school; B.A. in Biology, eventually leading to an interest in General Systems and computing; interest in robotics sparked by the realization that autonomous machines could enable a vast improvement in land management.

Machine Learning in Python: Principal Component Analysis (PCA) for Handling High-Dimensional Data In this video, I will be showing you how to perform principal component analysis (PCA) in Python using the scikit-learn package. PCA represents a powerful learning approach that enables the analysis of high-dimensional data as well as reveal the contribution of descriptors in governing the distribution of data clusters. Particularly, we will be creating PCA scree plot, scores plot and loadings plot. This video is part of the [Python Data Science Project] series. If you're new here, it would mean the world to me if you would consider subscribing to this channel.

Machine learning (ML) practitioners gather data, design algorithms, run experiments, and evaluate the results. After you create an ML model, you face another problem: serving predictions at scale cost-effectively. Serverless technology empowers you to serve your model predictions without worrying about how to manage the underlying infrastructure. Services like AWS Lambda only charge for the amount of time that you run your code, which allows for significant cost savings. Depending on latency and memory requirements, AWS Lambda can be an excellent choice for easily deploying ML models.

What's dangerous is not to evolve. The darling of consumers and investors alike, Mr. Bezos sure seems to have the future figured out. Amazon today is the most AI driven customer experience platform in the world, besides just being an e-commerce marketplace. Retail has moved from the brick-and-mortar store front to beautiful and highly aesthetic web portals, accessible on any device you use, that seem, at times, shockingly intuitive. The secret ingredient here is AI. The global e-commerce industry, running hosted servers and data-centers around the world has been changing paradigms in how the world shops, for the last five years, and the possibilities seem to be, pardon the cliché, limitless.

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