Kimi Founder Yang Zhilin on K2, Agentic LLMs, & AGI: The Beginning of Infinity | Scaling & Innovation Strategy — Neural intel Pod

✨ AI Summary

K2 model development emphasizes Token Efficiency using non-Adam optimization techniques like MOG optimizer to extract more intelligence from same data amount
Shift from 'Brain in a Vat' pure reasoning models to Agentic LLMs that interact with external environment through tools and multi-turn operations, enabling complex long-running tasks via Test Time Scaling
Path to AGI framed as direction rather than milestone, with conceptual L1-L5 hierarchy emphasizing critical need for using AI to train AI (L4 Innovation) to solve generalization challenges for agents