In this video I break down recent research exploring metacognition in large language model ensembles and the growing shift toward System 1 / System 2 style AI architectures.
Some researchers are no longer focusing on making single models bigger. Instead, they are building systems where multiple models interact, critique each other, and dynamically switch between fast heuristic reasoning and slower deliberate reasoning. In other words: AI systems that monitor and regulate their own thinking.

Artificial metacognition: Giving an AI the ability to ‘think’ about its ‘thinking’
https://theconversation.com/artificia… System 1 to System 2: A Survey of Reasoning Large Language Models https://arxiv.org/abs/2502.17419 The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity https://dl.acm.org/doi/10.1145/374625… Emotions? Towards Quantifying Metacognition and Generalizing the Teacher-Student Model Using Ensembles of LLMs https://arxiv.org/abs/2502.17419 Metacognition https://research.sethi.org/metacognit… Robot passes the mirror test by inner speech https://www.sciencedirect.com/science… METIS: Metacognitive Evaluation for Intelligent Systems https://research.sethi.org/metacognit… Distinguishing the reflective, algorithmic, and autonomous minds: Is it time for a tri-process theory? Get access Arrow https://academic.oup.com/book/6923/ch… #science #explained #news #research #sciencenews #ai #robots #artificialintelligence.

From System 1 to System 2: A Survey of Reasoning Large Language Models.
https://arxiv.org/abs/2502.

The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity.
https://dl.acm.org/doi/10.1145/374625…

Emotions? Towards Quantifying Metacognition and Generalizing the Teacher-Student Model Using Ensembles of LLMs.
https://arxiv.org/abs/2502.