AI News, Retail's Adapt artificial intelligence
- On Tuesday, August 20, 2019
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AI New Retail: Recent Developments and Future Trends
The traditional retail industry is facing challenges as the rapid development and continuous improvement of AI tools and techniques ushers in the era of New Retail.
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.
With the promotion and widespread of human-computer interaction, NLP has become a hot research topic among giant retailers, supporting machine translation, text data mining, semantic computing, text searching, recommendation systems, etc.
Bundled with deep learning and machine learning algorithms, sensors allow retailers to perform high-dimensional big data analytics to boost sales and customer satisfaction in New Retail.
Alibaba: The company’s Alipay mobile payment solution has been strengthened with the tech giant’s patented technologies based on deep learning, biometric facial recognition, eye vein pattern recognition and so on, allowing customers to forego cash and simply scan and pay for items with their smartphones.
The company rolled out a delivery robot product that integrates cutting-edge technologies like 360-degree view monitoring and LiDAR detection to provide low-cost logistics services in over 20 urban areas in China.
Walmart: Based onblockchain, big data, and machine learning technologies, Walmart collaborated with Microsoft, IBM, JD.com, and Tsinghua University to develop a tracing solution for all its New Retail customers and suppliers, to ensure that all relevant information about products anywhere on the supply chain is trackable in real time.
Application of Robotics and Automation Technologies: Advanced AI, computer vision and sensor technologies enable the launch of robots and unmanned systems in retail scenarios, greatly reducing production and operational costs and improving customer shopping experience.
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