AI:AM — Human Tissue Models, Physical AI, and the Future of Testing · September 25, 2026
Notes de l’épisode
Vivodyne’s Andrei Georgescu explains how vascularized human tissue models, robotics, multi-omic measurement, and foundation models could improve drug testing before clinical trials. Archetype AI’s Nick Gillian discusses Newton, a Physical AI model that combines sensor data to understand and predict events in the real world; the hosts also examine AI product safety, OpenAI and Anthropic’s alignment philosophies, CRISPR research, and whether AI can deliver useful advances in biology before it is fully understood.
Chapters
(0:00) AI safety has two different meanings.
(0:15) Why drug testing needs human tissue.
(3:20) Physical AI is bigger than robots.
(5:01) Biology’s bar is lifesaving progress.
(11:17) Opening and AI news
(11:38) Jensen Huang’s safety argument
(13:24) The “just software” debate
(15:31) Why AI companies must mature
(21:12) Muse and product safety
(29:25) Testing AI agents in the real world
(29:35) Product safety versus existential risk
(29:45) The alignment philosophy problem
(38:34) OpenAI versus Anthropic
(40:36) When safety concerns converge
(41:55) Human tissue models
(44:12) Why organoids need realism
(47:35) Measuring tissue responses
(54:03) Mapping causal biology
(1:03:40) Improving drug development
(1:09:08) Foundation models and experiments
(1:12:18) TissueDisk and robotic labs
(1:12:28) Before clinical trials
(1:30:37) What is Physical AI?
(1:32:25) Beyond robots and cars
(1:35:33) Training on physical data
(1:38:04) Cleaning and aligning sensor data
(1:40:34) Human and machine outputs
(1:49:30) A river construction case study
(1:53:28) How Newton finds hidden patterns
(1:57:33) Zero-shot sensor adaptation
(2:01:16) Industrial impact and expert knowledge
(2:05:22) From machines to ecosystems
(2:14:10) Physical agents and superintelligence
(2:15:34) The big AI-biology question
(2:21:55) Specialists versus generalists
(2:23:39) Distilling frontier models
(2:33:33) AI discovers a CRISPR sequence
(2:39:22) Useful biology before theory
(2:45:10) From job displacement to progress
(2:46:44) AI diffusion and economic growth
Guests
Andrei Georgescu — CEO, Vivodyne (𝕏 | LinkedIn)
Nick Gillian — CTO, Cofounder, Archetype AI (𝕏 | LinkedIn)
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