Edo is the founder of HyperCube, an early-stage startup in the machine learning and cloud computing space. He was a Director of Research at AWS and the head of Amazon AI Labs. He led the creation of Amazon SageMaker and its Elastic Algorithms suite. He was also the science director supporting Amazon Elastic Search, Kinesis, Glue, QuickSight, Personalize, Forecast, DeepRacer and other AWS services. Prior to that, he managed Yahoo’s independent research lab in New York and its scalable Machine Learning Platforms group. Edo also co-founded an automatic video content recognition startup which was later acquired by Vizio. Edo Liberty received his B.Sc. in Physics and Computer Science from Tel Aviv University and his PhD in Computer Science from Yale University, where he was also a postdoctoral fellow in Applied Mathematics. As an adjunct professor at Tel Aviv University, Edo taught advanced data mining algorithms. He is the author of more than 75 academic papers and patents on topics such as machine learning, data mining, streaming algorithms, and optimization. His publications include award-winning breakthroughs on streaming matrix approximation and fast dimension reduction. He is a frequent program committee member and invited keynote speakers at international academic and developer conferences.
Keynote Title: Benefits and Challenges of combining Deep Learning and Search
Abstract: Deep Learning has fundamentally changed Information Retrieval. Traditional search retrieves text documents based on text queries. Today, however, companies want to search for images, videos, customers, jobs, shopping catalog items, friends, places, and many more. For such searches, Deep Learning models provide the most accurate results. Unfortunately, deploying and serving machine learning models at massive scale is still a herculean effort even for highly tech-heavy companies. This talk will survey some of those challenges. We will also introduce a new cloud-managed service by HyperCube which serves such real-time workloads.