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An Introduction to Multi-Agent Systems

An Introduction to Multi-Agent Systems

A multi-agent system (MAS) is a computational framework consisting of multiple interacting agents or autonomous entities, each with its own goals, knowledge, and decision-making capabilities. These agents can be software programs, robots, or any other smart entities that can perceive their environment, reason, learn, communicate, and take actions to achieve their objectives.

GPT Few-Shot Learning

GPT Few-Shot Learning

GPT few-shot learning refers to the ability of Generative Pre-trained Transformer (GPT) models to learn and generalize from a small number of examples or training instances, also known as “few-shot learning.” In the context of GPT models like GPT-3, few-shot learning demonstrates the model’s capacity to understand and perform tasks with very limited guidance or additional training.

ChatGPT Fine Tuning

ChatGPT Fine Tuning

ChatGPT fine-tuning refers to the process of refining a pretrained language model, such as OpenAI’s GPT (Generative Pre-trained Transformer), for a specific chatbot or conversational AI application. Fine-tuning involves training the model further on a narrower dataset, which is curated or generated based on the intended purpose and domain of the chatbot.

AI Agents

AI Agents

AI agents are autonomous or semi-autonomous software programs that utilize artificial intelligence techniques to perform various tasks, make decisions, and interact with their environment or other agents.

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