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DeepMind’s Talker-Reasoner framework brings System 2 thinking to AI agents
Talker-Reasoner is inspired by the two-system thinking cognitive framework proposed by Daniel Kahneman.
In a new paper, researchers at Google DeepMind introduce Talker-Reasoner, an agentic framework inspired by the “two systems” model of human cognition. It is primed to perform specific tasks and interacts with tools and external data sources to augment its knowledge and make informed decisions. The AI coach interacts with users through natural language, providing personalized guidance and support for improving sleep habits.
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