Cognitive Architectures of AGI: 7 Patterns That Transform LLMs from Oracles into Thinkers

Short summary

Modern LLMs transition from oracles to active thinkers via cognitive architectures combining verification loops, multi-agent swarms, and meta-learning. Seven patterns—adversarial resonance, markov blankets, cognitive stability, meta-learning topology, agent swarms, verification loops, and instrumental convergence—enable models to crystallize truth from probabilistic noise. Practical techniques like chain-of-verification and multi-agent architectures are immediately applicable to LLM product design.

• •Seven cognitive architecture patterns enable LLMs to shift from passive oracles to active thinkers
• •Verification loops, multi-agent swarms, and meta-learning collapse probabilistic noise into structural truth
• •Immediately applicable techniques like chain-of-verification and agent swarms improve LLM product design

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