Today’s AI assistants provide answers to questions or perform simple, well-defined tasks. But they do not act independently. In addition, more complex tasks always require a human to act as a supervisor. AI agents, on the other hand, should find a solution on their own and pursue goals autonomously or semi-autonomously.
AI agents use basic models for language, image recognition, and more to take instructions in natural language and process complex tasks. They use various tools such as browsers, search engines, and code compilers to achieve their goals. They can adapt to new situations and learn from experience.
For example, an AI agent could be given the task of creating a market research report. It would then independently search the web, analyze data, identify trends, and write a structured report-all based on a simple instruction from the user. Working semi-autonomously, the agent would check in with the user at certain points to confirm interim results or get further instructions.