Deep Learning is disrupting decades' worth of data infrastructure building. Specifically, we will look at retrieval problems. These are core to similarity search, deduplication, recommender systems, matching, feed ranking, personalization, and many more. While deep learning can unlock greater relevance and accuracy, it also presents significant operational and scientific challenges. Collecting data (correctly) is far from being trivial because of complex data interactions, training new models requires scale and distribution that most companies are not comfortable using, and real-time serving (efficiently) is almost impossible with tools that exist today. We will deep-dive into how HyperCube is thinking about unifying these applications under a single abstraction and a unified system.
Edo Liberty 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, Edo managed Yahoo’s 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 speaker at international academic and developer conferences.