Prakash Narayanan and Nathan Labenz speak with Sergey Edunov of Genesis Molecular AI and Michael Förtsch of Q.ANT about two fronts in applied AI: drug discovery and photonic computing. The conversation covers molecular foundation models, wet-lab data, assays, evaluation, memory and data movement, and how light-based processors compare with quantum hardware.
Chapters
(0:00) AI learns when to cheat.
(0:51) Great scores can still fail.
(2:08) The processor isn't the power hog.
(2:49) Who checks the AI trainer?
(3:37) Opening and morning context
(3:56) Why AI models cheat
(10:54) Chain-of-thought monitoring
(17:11) AI-written op-eds
(19:25) Claude writing workflow
(22:46) Physical AI and physics
(26:38) Multimodal scientific discovery
(30:11) Sergey Edunov and Genesis
(32:18) Claude's molecular binder demo
(36:11) The drug discovery pipeline
(42:14) When accuracy becomes useful
(44:32) Wet labs and training data
(47:06) Pharma AI deal structures
(48:47) Biology model architectures
(53:45) Data scarcity and physics
(54:47) Coding agents and human taste
(58:11) Scaling laws and evaluation
(1:02:33) Assays and data quality
(1:03:54) Multimodal molecular models
(1:09:59) Benchmarks versus progress
(1:16:24) Meet Michael Förtsch and Q.ANT
(1:18:11) Why photonic computing
(1:22:28) Memory and data movement
(1:26:30) How light performs computation
(1:31:42) Porting PyTorch to photonic chips
(1:35:32) Scaling photonic hardware
(1:44:01) Legacy fabs and manufacturing
(1:56:00) Quantum versus photonic computing
(2:02:45) AI inside Q.ANT
(2:12:09) OpenAI's Jalapeno chip
(2:14:16) NVIDIA's performance race
(2:16:32) Demand for intelligence
(2:17:59) Ethereum's GPU price cycle
(2:19:26) AI for discovery
(2:20:45) Contextualizing AI hype
(2:23:41) Why RL teaches cheating
(2:28:28) Data quality and model integrity
(2:29:58) Why RL deployment is limited
(2:31:26) The microscope analogy
(2:32:59) Recursive self-improvement risk
(2:34:27) AI's persistence advantage
(2:36:10) Why monitors are not ready
Guests
Michael Förtsch — CEO and Founder, Q.ANT (𝕏 | LinkedIn)
Sergey Edunov — CTO, Genesis Molecular AI (𝕏 | LinkedIn)
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