1 ML Services on the Public Cloud Not all ML services are built the same. As a consultant working in the public cloud, I can tell you that you are spoilt for options for Artificial Intelligence (AI) / Machine Learning (ML) tooling on the 3 big public clouds - Azure, AWS, and GCP. It can be overwhelming to process and synthesize the wave of information; especially when these services are constantly coming out with new features.

1 Problem of Information Overload All of us are no stranger to search engines and recommender systems. Without them, we would get overwhelmed with the sheer amount of information being created every second. This information could take different data formats - text, images, audio, video etc. Fundamentally, these systems can, given a large catalog of information, surface, filter and rank the relevant items based on the user’s query or profile, enabling us to navigate a sea of items, where otherwise users would struggle with information overload.