Ep. 96 Excerpt 4: Gain Competitive Edge in AI Through Data Annotation and Labeling

In this excerpt from episode 96 of the Digitally Irresistible podcast, strategic advisor Joe Buggy discusses the process of training an AI model. He explains that the first steps involve collecting data, ingesting it into a system, and potentially categorizing or transforming it for better organization. The critical step of labeling and annotating the data helps provide structure and context, which is essential for training the AI to predict or perform tasks accurately. After the model is trained, it must be run multiple times to validate its output and ensure it aligns with expectations based on the input data. Finally, Joe emphasizes the importance of continuous monitoring and updating of the AI model, as new customer data and context are constantly being added to make the model more robust in their world.