Summary
I thoroughly enjoyed my discussion with Charles and, in particular, delving into some of the technical nuances of the research and development he is doing on new tools such as WeightWatcher, which help us better understand AI models.
Charles is a straight shooter. He makes the point that it’s important to ask yourself, if you’re looking at working with or going into a company, whether the leaders are open to change or whether are they just going to keep doing what they’ve always done. Another key issue that he raises, which I come across often, is a lack of understanding among senior executives and leaders about how data science works. For one, you can’t simply apply software engineering practices and management paradigms to data science. They tend to be rigid processes that are not directly “science” projects, and they can hinder the development and productionization of data science models. Data science and AI are not commoditized...