技術

Chain-of-Thought (CoT)

定義

A prompting technique that encourages an LLM to articulate its reasoning step by step before producing a final answer. CoT significantly improves performance on multi-step reasoning, mathematics, and complex decision-making tasks.

関連用語

Prompt Engineering

The practice of designing and optimising input prompts to elicit the best results from AI models, especially LLMs. Structured prompting—using system instructions, examples, and constraints—can dramatically improve output quality without changing the underlying model.

Large Language Model (LLM)

AI models trained on vast amounts of text data that can understand and generate human-like text. Examples include GPT-4, Claude, and Llama. LLMs power modern chatbots, content generation, and code assistance tools.

Agentic AI

AI systems that autonomously plan, reason, and execute multi-step tasks over extended time horizons without continuous human direction. Agentic AI is moving from demo to production in 2025–26, raising new questions around oversight, auditability, and the EU AI Act's human oversight requirements.

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