Advanced AI systems capable of performing tasks in the real world.
In AI, "agents" refer to systems that can autonomously perform tasks, make decisions, and interact with the environment in a meaningful way. They represent the next step in AI development, moving from passive tools to active assistants in various domains such as home automation, personal assistance, and customer service.
An AI becomes an agent when it can operate independently, interact with its environment, and perform tasks without direct human oversight.
Yes, with advancements in machine learning, agents are designed to learn from interactions and improve their performance over time.
An instruction or set of guidelines given to an AI model to define its behavior, tone, or constraints for a session.
Language models enhanced with external knowledge sources, such as embeddings or vector databases, to improve performance in tasks like retrieval and question answering.
Learn how thresholds work in AI chatbots to control confidence levels, trigger actions, and improve response accuracy in your applications.
Learn how grounding connects AI responses to verified data sources, reducing hallucinations and improving accuracy in your AI chatbot.
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