There is a general understanding that it is becoming increasingly difficult to extract meaning from all the data we are collecting without using AI.

But what is AI, and how did we end up in a situation where it is identifying wolves from dogs based on the presence of snow in the background of images? 

What does this mean for spatial analysis using tabular data? 

What is explainability? 

This is not a "how-to" do spatial analysis using an AI episode, it is an overview of  AI in spatial analysis episode with Vin Sharma, VP of Engineering at FourSquare 

https://www.linkedin.com/in/ciphr/

https://foursquare.com/