This session will explore how investments and bold bets in accelerated computing, data generation at scale, and model-first strategies are revolutionizing the industry, without ignoring the initial challenges. Panelists will discuss the role of foundation models (FMs) in identifying new drug targets through the creation of massive multi-modal datasets, alongside the applications of generative AI in the design of small molecules, antibodies, and other therapeutic modalities. Additional topics to be discussed include notable successes and real benchmarks within the industry, demonstrating how these innovations have led to reduced costs, accelerated cycle times, and improved timelines from target identification to Investigational New Drug (IND) applications. This session will examine the pivotal role of accelerated computing in reshaping the future of drug discovery and development, fostering collaborations that will propel the pharmaceutical industry forward.