AI Approaches (a.k.a. AI word salad)
I’ve been struggling to summarize artificial intelligence (AI) for my clients (and for myself!). Its methods and vocabulary are vast and intricate, grounded in mathematical and neuroscience concepts, and continually evolving with fresh insights from research labs and academia. To navigate this complexity, with the help of my faithful assistant (ChatGPT), I’ve created the following two tables that provide an overview of the approaches and technologies used. I’ve taken some liberties in organizing the tables into a two-dimensional space, though the reality is that the lines are blurred, and some concepts span multiple cells. The Basics: Traditional AI vs. Deep Learning Traditional AI, grounded in statistical and mathematical methods, offers a reliable approach for tasks such as predictive analytics, classification, clustering, and anomaly detection. It’s like having a well-oiled machine—efficient, interpretable, and requiring less data to function effectively. On the other hand, De...