Sara Hooker on the End of Static AI
Sara Hooker on the End of Static AI  
Podcast: The Information Bottleneck
Published On: Wed Sep 16 2026
Description: What comes after scaling?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.TopicsContinuous learning and adaptive AIFine-tuning, memory, and AutoScientistAI agents and automated researchNon-verifiable tasks and human feedbackAdaptive interfacesOpen vs. closed models and distillationAI safety, regulation, cyber risk, and bioriskAI companionship and persuasionThe limits of TransformersMultilingual models and tokenizationChapters00:00 — Introduction02:15 — Why start another AI lab? The return of research05:46 — What continuous learning actually means12:04 — Should every company have its own adapting model?13:59 — Fine-tuning and platforms like Tinker18:04 — AutoScientist and automated optimization22:52 — Can AI really improve its own research?28:38 — The problem of non-verifiable tasks31:30 — Human feedback and the limits of exponential progress34:43 — Why the AI interface matters40:36 — Distillation, China, and open models49:05 — Open-model licensing52:19 — Will open models catch closed models?58:43 — AI regulation and compute thresholds1:03:07 — AI safety and agent failures1:10:19 — Biorisk vs. cybersecurity1:14:03 — Persuasion, AI companionship, and overlooked risks1:20:41 — Where will AI have the biggest real-world impact?1:25:41 — What is missing from current AI architectures?1:29:03 — Neurosymbolic AI1:31:30 — Multilingual models and tokenization1:34:02 — Byte-level models and alternatives to tokenization1:35:03 — ClosingMusic"Kid Kodi" - Blue Dot Sessions - via Free Music Archive - CC BY-NC 4.0