There’s been a great work in the ML research in the last decade. What we see the last 3 years is a new movement orthogonal to ML, ML Ops. ML Ops is still in its infancy but its premise is how to create a ML infrastructure that will promote best practices and expedite ML projects. ML practitioners can been seen as chefs; they need the proper tooling to unveil their talent. However, the interface of this tooling is crucial in order to make them useful to ML practitioners. In this talk, I’ll provide my view on the importance of ML APIs.