Scoring your business in the AI matrix (sponsored by Dataiku)

One widely accepted definition of AI is that it means going beyond simple statistics to mimic human skills in perception, learning, interaction, and decision making. Jed Dougherty tightens up this definition by sharing examples on a matrix that breaks down the different parts of that definition and how they might manifest themselves in data science projects at different levels.

AI is certainly a hot topic—everyone claims to be doing it (or at least working on doing it). But how many businesses are actually executing? One of the reasons it’s a difficult question to answer is that everyone seems to have a different definition of what exactly AI is. One of the more common and fairly widely accepted definitions is that AI means going beyond simple statistics to mimic human skills in perception, learning, interaction, and decision making. But even this definition leaves some room for interpretation. So going one step further, Jed Dougherty shares examples on a matrix that breaks down the different parts of that definition and how they might manifest themselves in data science projects at different levels. This keynote is sponsored by Dataiku.