Despite a growing level of interest in mathematical optimization and decision intelligence, one thing that has been holding the field back is a significant skills gap—a topic I explored in greater depth in myof skills: understanding a complex business problem, identifying an opportunity for improvement, building a model that captures that opportunity, and then assessing and refining that model based on the observed results.
We've seen a lot of evidence that it can provide answers to textbook problems, but those are often phrased so carefully that they are just begging to be answered correctly by a machine. To make things a bit more interesting, we chose a sampling of user questions from our community forum, where the questions aren’t usually stated quite as meticulously as in a textbook.
It’s always a bit dangerous to make predictions about something that is evolving as rapidly as GenAI, especially given the two very different experiences we had with versions that were released just a few months apart. With that caveat in mind, I'll share my own recent experiences and also touch on more fundamental limits.
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