Glossary
Welcome to the Recivia.ai Glossary! Whether you're new to the world of AI or simply looking to better understand Retrieval-Augmented Generation (RAG) and related technologies, we've compiled this jargon-free guide to help you navigate the terminology.
A field of computer science that enables machines to simulate human intelligence, including learning, reasoning, and problem-solving. Generative AI is a subset of AI focused on creating content like text, images, and insights.
Data that serves as a foundation for AI-generated content, ensuring accuracy and relevance. In RAG, this means using your proprietary data to "anchor" outputs.
The tendency of an AI model to favor certain outcomes based on the data it was trained on. This can result in unfair or incorrect outputs if the training data is unbalanced.
The tools and processes used to analyze data and provide actionable insights for business decision-making. Generative AI can enhance BI by making insights accessible to everyone in an organization.
An AI-powered tool that communicates with users in natural language. Recivia.ai uses similar conversational interfaces to make data retrieval easy and intuitive.
Hosting AI solutions on the cloud, allowing users to access them via the internet. Recivia.ai supports cloud, hybrid, and on-premises deployments to suit your security and scalability needs.
A specialized AI model fine-tuned to a specific industry or business area. For example, a healthcare domain model might create patient wellness plans, while a finance domain model could forecast market trends.
Ensuring sensitive information is protected from unauthorized access. Recivia.ai prioritizes robust encryption and compliance with privacy standards to keep your data secure.
A mathematical representation of text, images, or other data that allows AI to understand relationships and context. Used in RAG to connect queries to the most relevant information.
AI solutions tailored for businesses to improve operations, decision-making, and efficiency. Unlike consumer AI, enterprise AI integrates with proprietary systems and data.
Customizing a pre-trained AI model for a specific task or domain using smaller, targeted datasets. Recivia.ai fine-tunes models to align with your business's needs.
A large, pre-trained AI model that serves as the starting point for fine-tuning. These models are trained on vast amounts of general data and require adaptation for specific tasks.
When an AI generates incorrect or nonsensical outputs, often because of gaps in its training data. Recivia.ai reduces hallucination by anchoring AI responses to accurate, proprietary data.
A mix of cloud and on-premises AI infrastructure, offering flexibility in scalability and data security.
The process of using an AI model to generate predictions, insights, or content. In RAG, inference combines retrieval of data with generative outputs to create accurate and relevant results.
A search system powered by AI that understands context, intent, and relationships, delivering precise and actionable results. Recivia.ai's search functionality goes beyond keywords for better insights.
An AI model trained on extensive datasets to understand and generate human language. Examples include GPT-4 and Google’s PaLM.
The time it takes for an AI system to process a request and deliver a result. Optimized systems, like Recivia.ai, minimize latency for fast, real-time outputs.
AI capable of processing and understanding multiple types of inputs, such as text, images, and videos, to create comprehensive outputs.
The art of crafting effective inputs (prompts) to guide AI systems in generating the desired output. At Recivia.ai, we optimise your prompts to get more accurate and useful results.
A hybrid AI system that combines:
- Retrieval Models: Pull information from a database or document source.
- Generative Models: Create outputs based on the retrieved information.
RAG ensures AI responses are both relevant and grounded in accurate data.
A security measure ensuring only authorized users can access specific AI functionalities or data.
The practice of encrypting and protecting data to prevent unauthorized access, a priority for Recivia.ai.
A data storage system optimized for managing vector representations of information. Vector stores allow AI to efficiently find the most relevant data.
By understanding these terms, you can make informed decisions about how Recivia.ai AI and RAG systems like can transform your business operations. Explore the glossary whenever you encounter a term or concept you'd like to understand better.
