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Generative AI agents has a significant advancement in the field of artificial intelligence, combining the autonomous decision-making capabilities of agents with the adaptability and creative problem-solving powers of generative AI models like large language models (LLMs).
When using an LLM like GPT-4, you might ask a factual question like, “What is sun?” The model can answer accurately because it was trained on a vast corpus of data.
However, if you ask a highly personalized question, such as, “How old is my dog?”, the model may falter because it lacks specific knowledge about the dog or access to your personal information.
This is where an AI agent shines. By integrating external tools or resources, the agent can fetch the required data and provide a precise answer.
