Demystifying AI: Your Go-To Glossary

Navigate the complex world of artificial intelligence with ease. Our curated glossary breaks down key terms and concepts, helping you stay informed in the rapidly evolving AI landscape.

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I

Internet of Things (IoT)

Refers to a network of physical devices, vehicles, appliances, and other objects that are embedded with sensors, software, and network connectivity, allowing them to collect and exchange data with other devices and systems over the internet.

J

JAIS

JAIS is an open-source large language model developed in the United Arab Emirates, specifically designed to understand and generate text in both Arabic and English. It is named after Jebel Jais, the highest mountain in the UAE, and is intended to bring the benefits of generative AI to the Arabic-speaking world.

L

Large Language Models (LLM)

A large language model is an advanced AI system trained on huge amounts of text to understand, generate, and interact using human language. It can answer questions, write content, and assist with many language-based tasks in a natural, conversational way.

L

Latency

Refers to the delay or time it takes for a system or process to respond to a request or input. In the context of AI, it's the time between when a command is given and when the system reacts.

L

Least-to-Most Prompting

Least-to-Most Prompting is a simple AI technique that breaks tough problems into easier steps, solving them one by one. Each step uses answers from the previous ones to build toward the full solution, making complex tasks manageable.

L

Log

Record of events, activities, or data points that are generated by an AI system or its components. It's like a digital diary that tracks what the system is doing, helping in debugging, monitoring, and optimizing its performance.

M

Machine Learning

Machine learning (ML) is a subset of artificial intelligence (AI) that enables computers to learn from data and improve their performance on specific tasks without being explicitly programmed. It's like teaching a computer to make decisions or predictions based on experience and data.

M

Meta

Formerly known as Facebook, Inc., is a technology company that plays a significant role in the development and application of artificial intelligence across various platforms. It is particularly known for its advancements in natural language processing, computer vision, and generative AI.

M

Microsoft Azure

Cloud computing platform that offers a wide range of services, including artificial intelligence, to help developers and organizations build, deploy, and manage intelligent applications. It's like a comprehensive toolkit for creating and scaling AI solutions in the cloud.

M

Mistral AI

French artificial intelligence startup that specializes in developing and providing large language models and generative AI solutions. It offers both open-source and commercial models, known for their efficiency, customization, and multilingual capabilities.

N

N-shot Learning

N-shot learning is a machine learning approach where a model learns to handle new tasks using only a small number (N) of labeled examples per class. It's especially useful when collecting large amounts of data isn't practical, allowing AI to generalize quickly from minimal input.

O

One-Shot Prompting

A prompt engineering technique where you provide an AI model with a single input–output example alongside your instruction. This example acts as a template, showing the model the exact format, tone, and logic you expect — helping it deliver more accurate results than instructions alone.

O

OpenAI

Research organization and company focused on developing and directing artificial intelligence in ways that benefit humanity. It's known for creating advanced AI models like ChatGPT and DALL-E.

P

Parameter-Efficient Fine-Tuning

A technique for adapting a pretrained AI model to new tasks by updating only a small fraction of its parameters — keeping the rest frozen. This approach saves time, memory, and computing power while achieving results close to training the entire model from scratch.

P

Performance Optimization

Process of improving an AI model's efficiency and effectiveness. It's all about making your AI assistant smarter, faster, and more accurate over time. It's like fine-tuning a machine to run smoothly and deliver better results.

P

Perplexity

AI-powered search engine and conversational research tool designed to provide accurate, comprehensive, and verifiable answers to user queries. It acts as a research partner, summarizing information from the internet and citing trusted sources.

P

Presence Penalty

Parameter used in generative AI models to control the repetition of tokens, words or phrases in the generated text. It discourages the model from using the same elements multiple times, promoting diversity and novelty in the output.

P

Prompt

A prompt is the input given to an AI system, guiding its response. It's like a conversation starter or task instruction for your AI assistant, setting the stage for interaction.

P

Prompt Caching (Prompt Catching)

Often written as "prompt catching," the correct term is prompt caching. It's a performance optimization where an AI provider stores the unchanged beginning of your prompt—like system instructions or reference documents—so it doesn't need to reprocess them on every request, saving time and money.

P

Prompt-Verkettung

Prompt chaining is a method that breaks a complex task into smaller, connected steps, guiding AI through each stage to produce more accurate and detailed results. Each step builds on the previous one, making it easier to manage and refine the output .

P

Prompt Compression

Prompt compression is the process of shortening the instructions you send to an AI model while keeping all the meaning intact. By reducing the number of tokens, it helps cut costs, speed up responses, and make better use of the model's context window.

P

Prompt Drift

Prompt drift is the gradual, often unnoticed shift in an AI system's output behavior over time—even when the original prompt hasn't visibly changed. It can result from model updates, accumulated conversation history, or evolving workflows, leading to inconsistent and unpredictable responses.

P

Prompt Engineer

A prompt engineer designs and refines instructions for AI systems to help them generate accurate, useful, and relevant responses. This role bridges the gap between human needs and AI capabilities, making interactions with artificial intelligence more effective and reliable

P

Prompt-Engineering

Prompt engineering is the art and science of crafting effective prompts for AI systems. It's like being a skilled conductor, guiding the AI orchestra to produce the perfect symphony of responses.

P

Prompt Engineering Platforms

Tools that help users create, test, and manage instructions for AI models, making it easier to get accurate and useful results from artificial intelligence.

P

Prompt Governance

Prompt governance is the organized process of managing, reviewing, and updating the instructions given to AI systems, ensuring they remain accurate, safe, and aligned with company policies. It helps teams keep AI responses reliable and compliant in a simple, structured way.

P

Prompt Injection

Prompt injection is a security attack where crafted input tricks an AI model into ignoring its original instructions and following the attacker's commands instead. It exploits the model's inability to distinguish between trusted developer instructions and manipulative user input, potentially leading to unsafe or unintended outputs.

P

Prompt Library

A prompt library is a collection of curated prompts designed to interact with AI systems, ensuring consistent and efficient communication.

P

Prompt Management

Prompt management is the practice of organizing, versioning, and maintaining your AI prompts as shared, reusable assets — instead of burying them inside your code. It helps teams collaborate, test variations, and update prompts without touching the application itsel

P

Prompt Management Platform

A prompt management platform is software that lets teams create, store, version, and reuse the instructions (prompts) sent to AI models like GPT-4, Claude, and Gemini — without needing engineering involvement for every change. It replaces scattered prompts in code, docs, and chat history with a single, searchable, collaborative source of truth.

P

Prompt Metadata

Prompt metadata is extra information attached to an AI prompt that helps describe its context, purpose, and structure, making it easier for AI systems to understand and process the prompt accurately.

P

Prompt Mining

Prompt mining is the process of collecting and analyzing prompts people type into AI tools like ChatGPT. It uncovers hidden patterns, such as real user needs or buyer interests, to improve AI interactions and business strategies.

P

PromptOps

PromptOps is the practice of managing, testing, and optimizing prompts used in AI systems, ensuring they are reliable, consistent, and scalable for business and enterprise use.

P

Prompt Optimization

Prompt optimization is the process of systematically refining the instructions you give to an AI model so it produces more accurate, reliable, and useful responses. It combines clear wording, structure, context, and testing to get the best possible output from any language model.

P

Prompt Rot

Prompt rot is the gradual decline in an AI model's response quality as conversations grow longer or prompts become bloated. Over time, the model forgets earlier instructions, prioritizes newer text, and produces increasingly inconsistent or incorrect outputs. Think of it as your carefully crafted instructions slowly losing their power.

P

Prompt Sharing

Prompt sharing means exchanging instructions or questions used to interact with artificial intelligence, helping others get better results or ideas from AI tools. It’s a simple way to learn from each other and improve how we use AI together.

P

Prompt Variables

Prompt variables are placeholders in AI prompts that let you easily customize parts of your request, making it flexible and reusable for different situations.

P

Prompt Versioning

Prompt versioning is the process of tracking and managing changes to prompts used in AI systems, making it easy to organize, improve, and revert to previous versions for consistent and reliable results.

Q

Query

A query is a request for information or data, often used in databases and AI systems to retrieve specific answers or results.

R

RAG (Retrieval-Augmented Generation)

RAG, or Retrieval-Augmented Generation, is a technique that enhances the accuracy and reliability of generative AI models by fetching facts from external sources. It's like having a research assistant that ensures the AI's responses are grounded in up-to-date, verified information.

R

Reasoning

Ability of a system to draw inferences, make decisions, and solve problems based on the information it has been given. It is a fundamental aspect of AI that enables machines to think and act in ways that mimic human intelligence.

R

Recursive Prompting

Recursive prompting is a technique where you use the AI's response to shape your next prompt, creating a feedback loop that refines the output step by step. Instead of expecting a perfect answer on the first try, you build toward it through iteration.

R

Retriever

A retriever in AI is a component that finds relevant information from a large corpus of documents based on an input query, using semantic search to enhance the accuracy of responses.

R

Role Prompting

Role prompting is a simple way to guide AI by telling it to act as a specific person or expert, like a teacher or marketing manager. This shapes its responses to be more focused, matching the style and knowledge of that role.

R

Role Specification

Role specification is the practice of assigning a specific persona or expertise to an AI during interaction. It's like asking the AI to put on a virtual hat, transforming it into a subject matter expert for more tailored responses.

S

Search Engine

AI Software system that helps you find information on the internet by searching through a vast index of web pages.

S

Semantic Search

Type of search that understands the context and intent behind a search query, providing more relevant and accurate results.

S

Serverless

Cloud computing execution model where the cloud provider manages the infrastructure, allocating machine resources on demand, and the user is not concerned with server management. It's a paradigm that allows developers to focus solely on writing and deploying code without worrying about the underlying servers.

S

Similarity Threshold

A similarity threshold is a value that determines when two items are considered similar enough to be matched. It balances precision and recall in search results.

S

Snippets Library

The Promptitude Snippets Library is a collection of reusable text blocks in Promptitude, like style guides, audience profiles, glossaries, mission statements or brand guidelines, and more that you can insert into prompts or chats to save time and keep content consistent.

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We're continually expanding our artificial intelligence glossary. If there are concepts you think we're missing, let us know by emailing us at hello@promptitude.io, and we'll add them soon.

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