Artificial Intelligence Peer Group | Retrieval-Augmented Generation for Reducing Large Language Model Hallucinations

NMTC Artificial Intelligence Peer Group presents
Retrieval-Augmented Generation is one strategy for reducing Large Language Model Hallucinations.

An LLM (Large Language Model) hallucination refers to instances where a language model generates information that is inaccurate, misleading, or completely fabricated, despite being presented in a confident and authoritative manner.

These hallucinations can range from minor inaccuracies to completely false statements, and they occur due to various factors, including the model's training data limitations, biases in the data, or the inherent challenges in understanding context and factual accuracy.

RAG (Retrieval-Augmented Generation) is a technique designed to mitigate such hallucinations by combining the capabilities of a traditional language model with an external knowledge retrieval component.
Artificial Intelligence (AI) peer group serves as a collaborative platform where members exchange knowledge, discoveries, and insights related to the development, advancement, and ethical implications of AI technology. Conversations will include discussions, sharing research findings, and exploring innovative ideas surrounding machine learning, neural networks, natural language processing, computer vision, robotics, and other AI-related domains.

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