Chapter 2

m井芝

Chapter 2 (Architecture of AI Agents) & Case Studies  

This section delves into the technical backbone of AI agents, emphasizing four core components:  
1. Perception Module， Processes multimodal inputs (text, images, sensors).  
2. Reasoning Engine: Leverages LLMs (e.g., GPT4) for planning.  
3. Memory Unit: Stores short/long-term data for context-aware actions.  
4. Action Interface， Executes decisions via APIs or physical actuators.  

A case study on **AI agents in healthcare** impressed me—where systems like IBM’s Watson analyze patient data to suggest treatments, reducing diagnostic errors by 40%. The book also discusses "swarm agents" (multiple agents collaborating), used in climate modeling.  

Critique:
While the applications are promising, the book underplays challenges like energy consumption (e.g., training LLMs) and data bias.  
But I still have some question ，Could over-reliance on AI agents in critical fields (e.g., medicine) erode human expertise?