Digital pathology is the management and interpretation of pathology information in a digital environment that enables better, faster and cheaper diagnosis and prognosis of cancer and other diseases. With the advent of whole-slide imaging, the field of digital and computational pathology has gained a lot of traction, especially among the machine learning and image processing communities. Precision medicine, or personalized medicine, on the other hand aims to tailor treatments to individuals based on their unique characteristics, moving away from the one-size-fits-all approach of traditional medicine. In this lecture, I will discuss our work in developing computer-aided systems for breast cancer precision medicine from whole-slide pathology images.

The semiconductor industry is undergoing a profound transformation driven by increasing design complexity, accelerated product life cycles, and the growing need for innovation at scale. At the heart of this evolution lies the potential of Artificial Intelligence (AI) to revolutionize System-on-Chip (SoC) design. This speech explores how AI-driven methodologies empower design houses to stay competitive and agile in the face of mounting challenges.

As SoCs become more heterogeneous and densely packed with IP blocks—CPU clusters, AI accelerators, security engines, and high-speed interfaces—the complexity of design, verification, and optimization has grown exponentially. Traditional design methods are increasingly insufficient to manage this scale and pace. AI introduces intelligent automation across the SoC lifecycle—from RTL generation and floorplanning to timing closure and functional verification—resulting in faster iterations, improved performance-per-watt, and reduced time-to-market.

We have embraced this transformation firsthand through the development of our innovative SoCs from IOT, Edge, Client to Data Center SOC, each built using AI-assisted design techniques. Leveraging these approaches has significantly improved design quality, enhanced engineering efficiency, and enabled us to meet aggressive delivery schedules. By integrating AI into key phases of our development process, we’ve achieved higher confidence in first-pass silicon while empowering our design teams to focus on architectural innovation and product differentiation.

Ultimately, this presentation positions AI-augmented SoC design not just as a technological enhancement, but as a strategic necessity for design houses navigating the pressures of innovation, shrinking development windows, and increasingly complex chip architectures. Attendees will gain insight into real-world examples, current AI-enabled EDA tools, and how embracing these techniques can redefine the future of semiconductor design.