The tutorial explores the use of Clarifai's General Recognition model to efficiently perform bulk labeling and create a custom model using transfer learning. Through the example of labeling a dataset containing various animal species, the tutorial demonstrates how to speed up the annotation process by allowing the model to identify and label images swiftly, significantly reducing manual effort. The process involves confirming the presence of specific animals like horses, dogs, elephants, butterflies, and chickens, and addressing any unlabeled images to ensure comprehensive training. By leveraging transfer learning, a new 'animal-classifier' model is created, which is trained on the labeled dataset and tested on a fresh set of images, yielding high accuracy in predicting animal types. The tutorial concludes with a successful demonstration of the model's capabilities and encourages users to explore machine learning applications using these techniques.