All systems and applications are composed from basic data structures and algorithms, such as index structures, priority queues, and sorting algorithms. Most of these primitives have been around since the early beginnings of computer science (CS) and form the basis for every CS intro lecture. Yet, we might be in front of inflection point. A recent result by our group shows that machine learning has the potential to significantly alter the way those primitives are implemented and the performance they can provide.

In this talks, I will use index structures, such as B-Trees, Hash-Maps, and Bloom-Fiterns, as an example to explain the intuition behind learned data structures and algorithms, and outlines the potential consequences of this technology for industry.