AI agent is a software entity that can perform tasks, think logically, and make decisions based on its environment, inputs, and predefined goals. Generative AI agent takes an LLM model and integrates that into an agent workflow to perform complex tasks for better result.
Agent Characteristics
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AI agents can
(1) Plan and gather information through sensors, data inputs, or external APIs.
(2) Reason by using AI algorithms to process data and make decisions based on patterns, rules, or learned behaviors.
(3) Store and retrieve memory to improve their performance over time by learning from past experiences and adapting to new data.
(4) Decide and act by using tools autonomously and without constant human input.
In a multi-agent environment, an agent can invoke other autonomous agents to collaborate and achieve a common goal. Some companies are leading the way employing AI agents into their products. ServiceNow, the top digital workflow automation company, has concrete plan to integrate AI agents into its suite of premier products. This cutting-edge work will unleash unprecedented productivity 24/7 and drive more business values for the customers.
Another impressive example of AI agents at work is the AI Scientist system developed by Sakana AI. This system has developed and employed agents capable of conducting scientific research, executing experiments, generating code, and discovering new knowledge.
In summary, AI agent is an intelligent software system that can perform multi-step tasks autonomously, adapt to environmental feedback, and improve over time through learning. These agent-based systems are poised to unlock significant economic value in the near future.
