Ralf Gommers, Director @ Quansight Labs

Numerical computing and deep learning libraries for Python all offer array
(or tensor) data structures and associated compute functionality with
similar APIs. There are many subtle differences however, making it hard for
users to migrate from one library to another, or for library authors to
write code that supports multiple array libraries. The Consortium for
Python Data API Standards (https://data-apis.org/) just released a first
version of its array API standard - which aims to address these issues -
for community review.

In this talk, we will start with an overview of the full API surface, and
then focus on some of the key choices made, such as dtype casting rules and
which mutability features are supported. Finally we will look at how this
new API aligns with the current MXNet API.