We talk with Sara Hooker, co-founder and CEO of Adaptation Lab, about why the next generation of AI may look very different from today's static models. Sara argues that models should continuously adapt to new tasks, data, users, and environments—and that doing this efficiently will require rethinking much more than fine-tuning.
We discuss continual learning, AutoScientist and automated research, why non-verifiable tasks may become the next major bottleneck, and why interfaces could be as important as the models themselves. We also get into open vs. closed models, distillation and Chinese AI labs, AI regulation and safety, cybersecurity and biorisk, AI companionship, and what may eventually come after Transformers and tokenization.
Topics
Continuous learning and adaptive AI
Fine-tuning, memory, and AutoScientist
AI agents and automated research
Non-verifiable tasks and human feedback
Adaptive interfaces
Open vs. closed models and distillation
AI safety, regulation, cyber risk, and biorisk
AI companionship and persuasion
The limits of Transformers
Multilingual models and tokenization
Chapters
00:00 — Introduction
02:15 — Why start another AI lab? The return of research
05:46 — What continuous learning actually means
12:04 — Should every company have its own adapting model?
13:59 — Fine-tuning and platforms like Tinker
18:04 — AutoScientist and automated optimization
22:52 — Can AI really improve its own research?
28:38 — The problem of non-verifiable tasks
31:30 — Human feedback and the limits of exponential progress
34:43 — Why the AI interface matters
40:36 — Distillation, China, and open models
49:05 — Open-model licensing
52:19 — Will open models catch closed models?
58:43 — AI regulation and compute thresholds
1:03:07 — AI safety and agent failures
1:10:19 — Biorisk vs. cybersecurity
1:14:03 — Persuasion, AI companionship, and overlooked risks
1:20:41 — Where will AI have the biggest real-world impact?
1:25:41 — What is missing from current AI architectures?
1:29:03 — Neurosymbolic AI
1:31:30 — Multilingual models and tokenization
1:34:02 — Byte-level models and alternatives to tokenization
1:35:03 — Closing
Music
"Kid Kodi" - Blue Dot Sessions - via Free Music Archive - CC BY-NC 4.0
