Sunghee Yun (He/Him)

Co-Founder & CTO @ Erudio Bio, Inc., Co-Founder & Leader & Chair of Silicon Valley AI Nexus (AI Nexus), Advisor @ Korean American Semiconductor Professional Alliance (KASPA), CGO / Global Managing Partner @ LULUMEDIC, KFAS-Salzburg Global Leadership Initiative Fellow @ Salzburg Global Seminar, AI-Korean Medicine Integration Initiative Task Force Member @ The Association of Korean Medicine, Director of AI Semiconductor @ K-BioX, Visiting Professor @ Sogang University, Advisory Professor @ DGIST, Global Advisory Board Member @ Innovative Future Brain-Inspired Intelligence System Semiconductor of Sogang University, and Network Expert @ Gerson Lehrman Group

Abstract

Artificial Intelligence (AI) has compressed decades of progress into months: from the deep learning revolution to the Transformer, from ChatGPT to today’s agentic AI systems that autonomously plan, use tools, and execute long-horizon tasks. Yet the most consequential insights driving Silicon Valley’s decisions — where trillion-dollar capital is actually flowing, which technical bets are load-bearing versus decorative, and why the frontier you learn today will move before you ship — rarely appear in lectures, papers, or search results. Drawing on a career spanning Stanford University, Samsung Semiconductor, Amazon, and multiple Silicon Valley startups, this talk shares the ground-level view of the AI landscape as it stands in 2026, including the agentic shift now reshaping how software, science, and companies are built.

The talk then turns to what may be the largest opportunity of this era: the convergence of AI and biotechnology. Three exponential curves — foundation models that speak biology’s languages, breakthroughs like AlphaFold, and unprecedented data availability — are peaking simultaneously, opening a trillion-dollar market. But the window rewards a specific kind of builder. This talk offers a practical framework for separating unicorn potential from hype: platform versus point solution, AI that is load-bearing rather than decorative, regulatory strategy designed in from day one, proprietary data moats that cannot be reverse-engineered, and human welfare not as a constraint but as a strategic asset that unlocks non-dilutive capital and institutional trust.

Finally, the talk grounds these principles in a real case: Erudio Bio, a Stanford spin-out combining patented dynamic force spectroscopy with AI to generate 1000x more high-quality molecular binding data — recognized by a $1M Gates Foundation Grant and validated through hospital and research partnerships in Korea and the US, including Keimyung University Dongsan Hospital in Daegu. The message for founders, investors, and ecosystem builders in the room is direct: the scarcest resource in this moment is not capital, compute, or data, but founders who hold the full stack — theory, engineering, clinical reality, and human purpose. The companies that will define human health in 2035 are being founded in the next 24 months, and there is no reason they cannot start from Daegu.