Ai
Artificial Intelligence (AI) refers to computer systems designed to perform tasks that typically require human intelligence. These tasks include learning from experience, recognizing patterns, understanding language, and making decisions. AI systems range from narrow applications focused on specific tasks to broader systems with more general capabilities.
Large Language Models and Knowledge Graphs
Large Language Models (LLMs) are a significant class of AI systems trained on vast amounts of text data. Recent developments have focused on integrating LLMs with knowledge graph technologies to enhance information retrieval and reasoning. The Cocoindex framework represents one approach to building real-time knowledge graphs from document collections, using LLMs to extract and structure information.
AI Agents
Beyond static retrieval and reasoning, modern AI evolves into AI agents capable of autonomous action. Key developments include:
- Distinction from Chatbots: Unlike traditional chatbots that primarily generate responses, agents are distinguished by their ability to reason, take actions, and adapt dynamically to environments.
- ReAct Framework: A foundational pattern for agent behavior that combines reasoning (thought processes) with acting (tool usage or external queries), enabling more robust problem-solving workflows. See detailed notes in AI Agents Explained: ReAct Framework, Behavioral Types, and Google ADK.
- Behavioral Types: Categorization of agent behaviors based on their interaction patterns and autonomy levels.
- Google ADK: Development kits provided by platforms like Google Cloud Tech to facilitate the rapid building and deployment of these agents.