What's in this lesson: Explore architectures designed for deeper reasoning through chain-of-thought, tree-of-thought, and multi-step planning.
Why this matters: True AI reasoning goes beyond simple pattern matching, enabling agents to solve complex, novel problems autonomously.
Why this matters: True AI reasoning goes beyond simple pattern matching, enabling agents to solve complex, novel problems autonomously.
The Two Minds of AI
Human cognition operates in two modes: System 1 (fast, impulsive, intuitive) and System 2 (slow, methodical, analytical). For years, Large Language Models (LLMs) operated strictly as System 1 thinkers, predicting the next word based on learned patterns without true deliberation.
But what happens when an AI encounters a problem that requires planning, logic, and self-correction? It needs an architecture that supports reasoning.
Experiment: Ask a Math Question
User: "If I have 3 apples and eat 1, then buy 5 more, but drop half of them, how many do I have?"
AI: "You have 3 apples." (Quick, impulsive, incorrect)
AI: "You have 3 apples." (Quick, impulsive, incorrect)