The year 2023 has been transformational for deployment of artificial intelligence (AI) in nearly every domain of human inquiry. Robust, resilient, and reliable models trained on an unprecedented volume of high-quality training data have enabled rapid advancements in natural language processing (NLP), computer vision, and general AI capabilities. Advancements in GPU design and novel architectural approaches are paving the way for state-of-the-art (SOTA) AI models that are increasingly more interpretable, practical, and semi-autonomous. This renaissance-like period in AI has largely been shaped by the emergence of foundational models: general-purpose, pre-trained representations of our world, learned from different modalities (structured, semi-structured, and unstructured) and sources of data (images, text, code, etc.). Foundational models extract fundamental patterns in data and encode the relationship between text, images, and code in terms of entities, concepts, and their interactions within the data.