Continual Learning Is the Next Bottleneck | Rohan Anil (Core Automation )

Rohan Anil of Core Automation discusses the relationship between pretraining, reinforcement learning and learning after deployment. Drawing on his optimization work at Google and Anthropic, he examines why additional post-training, distillation and longer contexts may not solve continual learning. Other topics include second-order optimizers, distributed training, low-level coding agents and the difficulty of coordinating very large GPU clusters. Hosted by Ravid Shwartz Ziv and Allen Roush. Watch the full conversation on the publisher’s YouTube channel.