Use Cases – Page 2
Intelligent Automation: Pros/Cons, Use Cases & 5 Key Capabilities
What Is Intelligent Automation (IA)? Intelligent automation (IA) is the integration of artificial intelligence (AI), machine learning (ML), and robotic process automation (RPA) to create systems that can perform both routine and complex tasks. These systems improve over time by learning from data and user interactions, leading to increased efficiency and decision-making capabilities. By using […]
RAG vs. LLM Fine-Tuning: 4 Key Differences and How to Choose
What Is RAG (Retrieval-Augmented Generation)? Retrieval-Augmented Generation (RAG) merges large language models (LLMs), typically based on the Transformer deep learning architecture, with retrieval systems to enhance the model’s output quality. RAG operates by fetching relevant information from large collections of texts (e.g., Wikipedia, a search engine index, or a proprietary dataset) and fuses this external […]
Understanding RAG: 6 Steps of Retrieval Augmented Generation (RAG)
What Is Retrieval Augmented Generation? Retrieval-augmented generation (RAG) is a technique that connects a large language model to external data at the moment it generates a response, instead of relying only on what the model learned during training. The term traces to a 2020 paper, “Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks,” from a team at […]