A Note from Sung-Hou Kim
We will be gathering on Saturday, August 1, 2026, to reminisce about our shared experiences in Berkeley during our younger years, much as you may have at many similar gatherings over the years.
However, we find ourselves at the leading edge of a gigantic AI revolution that is beginning to transform our world. Artificial intelligence is poised to change, in both positive and negative ways, nearly every aspect of human life and work. Its effects will extend beyond our own species to influence countless other living organisms—including, in its own way, our small group gathering.
For this reason, I suggested to the organizers the challenging task of balancing our reminiscences with a town-hall-style discussion about AI. Most of us are not AI experts, but we all need to talk about how to navigate this shift. AI will soon be as ubiquitous as our cell phones, just several orders of magnitude more powerful, and we must learn how to leverage it to enhance our daily lives and our work.
— Sung-Hou Kim
All speakers: please introduce yourself and briefly share a memory of your Kim-group days.
★
Welcome & Special Introductions
10 min
Sung-Hou Kim — thanks to the organizers
Session I — AI Related to Work
10 am – noon · 110 min
1
AI and Chemical Drug Design
40 min
Debanu Das*, Lan Huang, Mike Milburn, Chao Zhang
Discussion topics
A preview of the panel — a moderated conversation on where AI stands in drug discovery, followed by open questions from the room.
10 min · Introductions & a short memory
20 min · Planned Q&A
5 min · Unplanned Q&A
5 min · Audience Q&A
Precision medicine — Mike Milburn
- The emerging importance of AI in precision medicine.
- AI patient reports and reimbursement.
- Multimodal patient data and genomic testing.
- If precision medicine has struggled to change patient treatment, how will AI help?
Adoption, gaps & the data economy — Debanu Das
- If you're using AI today, how? Where would you like to expand? If not, how and when do you plan to start?
- What shortcomings have you hit — both real science/technology gaps that still need filling, and the gap between reality and the prevailing hype?
- AI as a natural extension of compute and HPC: with much of it now commoditized and proprietary experimental data widely seen as king, how are your companies approaching business development and monetization around data generation and data partnering?
- How are you assessing infrastructure companies to layer on top of your proprietary data? What are your current business directions?
- AI companies seeking reach through royalties on AI-driven drug discovery (AIDD).
- Agentic AI for R&D — e.g. Anthropic's Claude for Science, AWS Bio Discovery.
- Circuit breakers and safety protocols in agentic AI, when agents call other agents.
Impact vs. inflection — Chao Zhang
- Why has AI delivered only incremental — rather than transformative — impact in small-molecule drug discovery?
- What would mark the true inflection point for AI-driven small-molecule drug discovery?
2
AI and Protein Drug / Non-Natural Molecule Design
40 min
Byung-Ha Oh*, Vaheh Oganesyan, Jingtong Hou, Jonas Lee
3
AI for Everyone
20 min
Steve Muskal*
Lunch Break · 12:00 pm – 1:00 pm · hosted by Rosie
Boxed lunches — eat in Tan Hall, head out to the courtyard, or walk to the Campanile for a view of the Bay Area. Please be back in Tan Hall by 12:50 pm.
Session II — AI, Academia & a Perspective
1 pm – 3 pm · 120 min
4
Planning Forward
15 min
Rosie Kim*
5
AI and Academia
40 min
Chris Kim* (US), Liang Tong (US), KyeongKyu Kim (Korea), Pedro Matias (EU), Joel Sussman (Israel)
6
Perspective: Scientific & Societal Impact of the Human Genome Project and AI
30 min
George Church
7
Sung-Hou's Present Projects
35 min
Sung-Hou Kim
* Moderator · Panelists: sign in (top right) to add or replace content on your talk below — a PDF, slides (PowerPoint/Keynote), a Word doc, an MP4 video, or a link (a webpage, Google Slides, or a YouTube video). Videos and YouTube play right on the page.