The Hematoxylin and Eosin (H&E) stained tissue microscopic glass slide is a 100-year-old technology that remains the universal standard for histopathological diagnosis by pathologists. With the advancement of Artificial Intelligence (AI), and especially Deep Learning (DL), the H&E stained tissue slide is beginning to show even greater value. For decades, pathologists have applied natural intelligence and deep thinking to morphological features highlighted by H&E staining to categorize and classify diseases into reproducibly recognizable entities. In some instances, AI has been shown to match the ability of expert pathologists and exceed the ability of nonexpert pathologists in tasks that require precise quantitation. Furthermore, by examining thousands of morphological features on hundreds or thousands of cases, AI algorithms can quickly identify subtle patterns that have eluded pathologists, allowing AI to ‘see’ things that pathologists cannot. In this paper, we will discuss some of the recent advancements in AI/DL and H&E pathology by demonstrating key applications to the clinical practice of pathology, followed by a discussion about new avenues that are being created by AI for H&E pathology.