Artificial intelligence is evolving rapidly, and just as many people began to grasp generative AI, a new concept has emerged: agentic AI. In a recent video, Ethan's Cloud & AI Academy breaks down the fundamental differences between generative AI and AI agents in simple terms.
Generative AI refers to models like GPT, LLaMA, and Grok that can create new content—text, images, code, and more—based on patterns learned from vast datasets. These models act as the "brain," generating outputs but lacking the ability to perform tasks autonomously.
AI agents, on the other hand, are systems built on top of large language models (LLMs) that can take actions in the real world. They use the LLM as a reasoning engine to plan, execute, and learn from tasks. For example, an agent might book a flight or send an email by leveraging the language model's understanding.
The video also discusses the future of AI, including the rise of small language models (SLMs) designed for specific domains such as finance and legal. These specialized models promise greater efficiency and accuracy for targeted applications.
Whether you're a student, developer, or tech enthusiast, understanding the distinction between generative AI and AI agents is crucial as the field continues to advance.