AI:AM — Human Tissue Models, Physical AI, and the Future of Testing · September 25, 2026

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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