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 (RAG)? Retrieval Augmented Generation (RAG) is a machine learning technique that combines the power of retrieval-based methods with generative models. It is particularly used in Natural Language Processing (NLP) to enhance the capabilities of large language models (LLMs). RAG works by fetching relevant documents or data snippets in response to […]