Excited to have my book Lean AI be featured in these excellent Forbes articles about matching AI models to business needs. The first article discussed business applications can benefit from supervised learning. The second article will discuss unsupervised learning. Again, refer to the Lean AI book’s Figure 5-1, included below, for an overview of the four key types of artificial intelligence (AI) leveraged in machine learning (ML).
Management AI: Matching AI Models To Business Needs, Supervised Learning Examples — Ad Pricing And Medical Imaging by David A. Teich.
Managers often have fun when talking to their technical staff. When it comes to artificial intelligence, that fun can have quote marks around it. A few years back, Nvidia CEO Jensen Huang was talking about a “Cambrian Explosion” of artificial intelligence algorithms. While the vast majority of those were in academia, many are making their way to the business world. That might make managers nervous during conversations. Well, relax. It’s not necessary to know about all the different algorithms. On the other hand, it does help to understand the classes of algorithms. The different classes lean towards solutions for different business problems, and it’s good to have a high level understanding of the links. Read more on FORBES.
Management AI: Matching AI Models To Business Needs, Unsupervised Learning, Customer Segmentation, And Association by David A. Teich.
Most managers, both line and even IT, do not need to understand the intricacies of machine learning. However, a high level knowledge will help their organizations understand that AI is a tool and must be linked to real business problems. Having an idea of how the high level classifications of ML link to real world issues can help focus both the technical and business staff to provide effective solutions. Read more on FORBES.
