Speaker "Eldar Sadikov" Details Back



AI as a Service at Scale: Retail Case Study


In this talk, we will discuss new, emerging applications of AI in the retail industry. The emergence of cloud infrastructure and programmatic software services makes it possible to integrate AI technology into almost every standard software module. Everything from dynamic product ranking to the prediction of individual user attributes and dynamic price optimization becomes a service invoked dynamically for each customer, in real-time, as they visit a retailer's web site, interact with an e-commerce mobile app, or open a retail email. As a case in point, we will illustrate how Jetlore's machine learning rank technology, previously available only to top search engines like Google, is currently utilized by some of the world's largest retailers to power millions of consumer experiences every day. At the end of the session, we will take a sneak peak at the future: how traditional software modules like authentication, code compilation, continuous integration, or system monitoring can all benefit from AI as a service at scale.


Eldar Sadikov is the co-founder and CEO of Jetlore, the leading predictive AI platform for retail and beyond. A Gartner Cool Vendor 2016, Jetlore brings machine learning and predictive ranking technology across various use cases for some of the world’s largest retailers such as eBay, Nordstrom Rack, One Kings Lane and more. Eldar is a computer scientist by training and, prior to Jetlore, developed predictive statistical models for big data at Stanford University, Google, and Microsoft. He holds a MS in Computer Science from Stanford University and left the Stanford PhD program to pursue entrepreneurship. Eldar has received numerous industry research awards including the WSDM 2012 Best Paper Award and Google's Best Research in Information Retrieval Award in 2009. As a thought leader in the application of AI and algorithms for large-scale data mining, Eldar actively advises technology and marketing leaders and is frequently invited to speak at retail and big data conferences.