AI:AM Highlights: Recursive Self-Improvement, Rushed and Vibe-Coded?
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In this episode of The Cognitive Revolution, experts discuss how AI development is changing as multiple models work together instead of a single model handling everything—for example, Inherent Laboratories uses a 27 billion-parameter model for science alongside GPT-5.5 for coding.
The main theme is that this division of labor between models becomes important for AI systems to improve themselves recursively, but the podcast also raises a critical question: if development moves too fast and builds on systems that aren't sufficiently reliable, this could undermine the entire idea of self-improvement. The episode covers everything from how to verify discoveries that humans may not be able to check, to infrastructure for AI agents that can act in the real world.
Vibekollen prepared this summary with AI from the original publication. The content belongs to The Cognitive Revolution.
