\n", "\n", "How Does Agentic AI Work?
\n", "Agentic AI uses a five-step process for problem-solving:
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\n", "- World: The first principles of the cosmos, planet, life, ecosystem, and intelligence are experienced in real time. Humanity has encoded these in the laws of physics, biology, sociology, and other domains.
\n", "- Perceive: AI agents gather information from the world via sensors, databases, and digital interfaces, extracting meaningful features and recognizing key entities.
\n", "- Reason: A large language model acts as the orchestrator, understanding tasks, generating solutions, and coordinating specialized models for functions such as content creation, visual processing, or recommendation systems. Techniques like retrieval-augmented generation (RAG) access proprietary data for accurate outputs.
\n", "- Act: By integrating with external tools and APIs, agentic AI quickly executes tasks based on its formulated plans. Guardrails ensure proper task execution—for instance, a customer service agent might auto-process claims up to a limit, with higher amounts requiring human approval.
\n", "- Learn: Agentic AI continuously refines itself through a feedback loop (a “data flywheel”), where interaction data enhances the models, enabling it to adapt and drive better decision-making and efficiency over time.
\n", "-- Nvidia
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