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The article examines the feasibility of recursive self-improvement in AI given computational constraints and criticizes AI companies for prioritizing profit over societal benefits.
This article explores abusing the VP8 video codec's prediction mechanisms to simulate NAND gates and construct arbitrary combinatorial logic circuits, demonstrating an exotic computational substrate.
This position paper clarifies that claims of Transformer Turing-completeness often rely on unrealistic scaling assumptions, and argues that in real-world fixed models, context management is the critical factor determining computational power.