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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.
This analysis updates the study of DeepSeek's research team, revealing that their talent pool has grown to 356 researchers with increasing citation impact and that over half have only Chinese affiliations, highlighting challenges for U.S. talent retention and independence.
A paper analyzing Claude Code reveals that its effectiveness comes from a simple AI loop surrounded by a robust infrastructure for tools, safety, memory, and recovery, rather than a complex AI brain. The study emphasizes that autonomy increases the burden on infrastructure.
OpenAI releases an analysis demonstrating that compute used in largest AI training runs has grown exponentially at a 3.4-month doubling time since 2012, representing a 300,000x increase and vastly outpacing Moore's Law. The analysis suggests this trend will likely continue and calls for increased academic AI research funding to address rising computational costs.