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This article offers an in-depth analysis of the Causal World Model (CWM) proposed by Aether AI (原识之智), arguing that the next AI paradigm will shift from correlation to causation. It discusses the theoretical foundations, technical architecture, and potential impact on video generation and embodied intelligence.
Professor Biwei Huang proposes a four-generation theory of AI paradigms, believing LLMs are just the first step, and the future lies in causal world models. Aether AI has completed a $20 million funding round, dedicated to building causal world models.
Loop Engineering will completely replace Harness Engineering in the coming months, becoming the hottest paradigm in AI.
Key takeaway from an interview with @badlogicgames and @mitsuhiko: self-improving software and building primitives so agents can mutate projects without forking is a paradigm worth exploring.
This article summarizes Karpathy’s core points at the Sequoia Ascent conference, highlighting that AI is a paradigm shift restructuring workflows rather than merely an acceleration tool. It introduces the concept of a "jagged edge" for model capabilities based on verifiability and economic viability, and predicts that future software will evolve into an agent-native architecture where LLMs serve as the logic layer and traditional code functions as sensors and actuators.