Navigate AI Tech with Promptitude.io Resources

AEO (Answer Engine Optimization)

The practice of structuring content so AI tools like chatbots and voice assistants can easily understand and use it to give direct answers to questions. It helps your information appear in quick, conversational responses instead of just search links.

Agentic AI

Agentic AI refers to artificial intelligence systems that act independently, make decisions, and adapt in real time to achieve specific goals, often without human intervention. These systems are designed to handle complex tasks and respond to changing environments in a flexible, autonomous way.

AI21 Labs

AI21 Labs is an Israeli company specializing in NLP and the development of advanced AI systems that can understand and generate natural language. It provides foundation models and AI solutions tailored for enterprise use.

AI Agent

An AI agent is a software system that acts independently to achieve specific goals, using artificial intelligence to make decisions, learn, and adapt as it interacts with its environment.

AI Aggregation

AI aggregation is the process of using artificial intelligence to collect, combine, and organize data from multiple sources, making it easier to analyze and draw insights from large amounts of information.

AI Assistant

An AI assistant is a digital tool that uses artificial intelligence to help users complete tasks, answer questions, and manage information through natural, conversational interactions.

AI Chaining

AI chaining connects multiple artificial intelligence models so that the output of one becomes the input for the next, allowing them to work together to solve complex problems in steps.

AI Chatbot

An AI chatbot is an advanced software system designed to engage in human-like conversations by understanding context, detecting user intent, and generating relevant and natural responses using technologies such as natural language processing (NLP), machine learning (ML), and natural language generation (NLG).

AI Governance

A set of rules, policies, and best practices that guide how artificial intelligence is developed and used responsibly, ensuring fairness, transparency, and safety for everyone involved.

AI Knowledge Management

AI Knowledge Management uses artificial intelligence to organize, store, and retrieve information, making it easier for people and organizations to access and use knowledge efficiently. It helps turn large amounts of data into useful insights, streamlining everyday tasks and decision-making

AI Poisoning

AI poisoning is when someone deliberately corrupts the data used to train artificial intelligence systems, causing them to make mistakes or behave in unexpected ways. It’s a hidden threat that can quietly undermine the reliability of AI models.

AI Prompt Management

AI prompt management is the process of creating, organizing, and refining instructions given to artificial intelligence systems, ensuring they deliver accurate and consistent results in various tasks.

AI Prompts

AI prompts are the instructions, questions, or inputs you give to an artificial intelligence model to guide its response. Think of them as a conversation starter — the clearer and more specific your input, the more useful and relevant the output you'll receive.

AI Systems

Computer programs designed to perform tasks that typically require human intelligence, such as learning, reasoning, and problem-solving. They're like smart machines that can think and act on their own.

AI Workflow Automation

AI workflow automation uses artificial intelligence to streamline and manage tasks, making processes faster, more accurate, and less reliant on manual effort. It helps businesses work smarter by automating repetitive steps and improving overall efficiency .

Amazon Bedrock

Fully managed service offered by AWS that enables developers to build and deploy generative AI applications using a variety of foundation models (FMs) and LLMs from leading AI companies. It simplifies the integration of AI capabilities into applications, providing a single API for accessing multiple models.

Analogical Prompting

Analogical prompting helps AI models reason like humans by generating their own similar examples before solving a problem. It's a simple way to boost thinking without needing pre-made examples.

Anthropic

Company and research organization focused on developing and applying artificial intelligence in a safe and beneficial manner. It's like a guardian of AI, ensuring that these powerful technologies are used responsibly.

API

Application Programming Interface is a set of rules, protocols, and tools that enable different software components to communicate and integrate AI capabilities. It's like a bridge that connects AI models to other applications, allowing them to share data and functions seamlessly.

Big Data

Refer to the vast and complex sets of data that are too large and intricate for traditional data processing tools to manage. It is characterized by its enormous size, speed of generation, diversity of types, and the value it can provide through analysis.

CAT (Computer-Assisted Translation)

Software that helps translators work faster and more consistently by storing previously translated content and suggesting matches when similar text re-appears, reducing repetitive work and improving accuracy.

Chain-of-Thought (CoT) Prompting

Chain-of-Thought Prompting guides AI models to break down complex problems into simple, step-by-step reasoning, much like human thinking. This technique improves accuracy on tasks needing logic or multi-step solutions.

Chunk

A chunk in AI is a small, manageable piece of data or information that is processed or analyzed as a unit.

Cohere

Canadian multinational technology company specializing in artificial intelligence, particularly in LLMs and natural language processing for enterprise applications. It provides a platform for businesses to deploy generative AI solutions securely and efficiently.

Content Chunking

Content chunking breaks large pieces of information into smaller, manageable segments while keeping key context intact. This makes it easier for AI to process and understand data, turning messy text into useful bits.

Context

Refers to the surrounding information or environment that provides meaning and relevance to the input or output of an AI model. It's like the backdrop that helps the AI understand the nuances and intentions behind the text or data it is processing.

Context Engineering

Context engineering is the practice of designing systems that strategically provide AI models with the right information, tools, and instructions to generate accurate and relevant responses.

Context Window

A context window is the amount of information an AI model can consider at one time when generating a response, similar to short-term memory. It helps the model understand and respond to your input more accurately.

Decomposed Prompting

A technique that breaks complex AI tasks into smaller, focused sub-tasks handled sequentially. Instead of asking an AI to solve everything at once, you guide it through step-by-step components, delivering more accurate and reliable results.

Deep Learning

Subset of machine learning and artificial intelligence that involves the use of artificial neural networks to learn from extensive datasets. It simulates human cognitive processes by using multiple layers of software nodes, or neurons, to process and analyze data.

DITA (Darwin Information Typing Architecture)

DITA (Darwin Information Typing Architecture) is an XML-based framework that helps organize and manage technical content into reusable, modular pieces. It enables teams to create once and publish across multiple formats without duplication.

Embeding Models

Embedding models turn complex data like text, images, or audio into lists of numbers, making it easier for AI systems to understand and compare information in a meaningful way.

Endpoints

Endpoints are specific access points where an application or service receives and responds to requests, usually through a URL or address. They act as doors that let different systems talk to each other in a clear, structured way.

Enterprise AI

Enterprise AI refers to the application of artificial intelligence across an entire organization to streamline operations, automate workflows, and enhance decision-making at scale. It goes beyond individual AI tools by including the governance, security, and infrastructure needed to deploy AI reliably in real business environments.

EU AI Act

The EU AI Act is the world's first comprehensive law regulating artificial intelligence. It classifies AI systems by risk level — from minimal to unacceptable — and sets clear rules for developers and users to ensure AI remains safe, transparent, and respectful of people's rights across Europe

Few-Shot Prompting

Few-shot prompting is a simple way to guide AI by including a few examples in your prompt. It helps the model understand a task quickly without needing lots of training data, making responses more accurate and on-point.

Fine-Tuned Model

Pre-trained model that has been further trained on a smaller, task-specific dataset to adapt it to a particular use case or domain. This process enhances the model's performance and relevance for the targeted task.

Frequency Penalty

Parameter used in LLM to control the likelihood of word (tokens) repetition in general context of the generated text. It discourages the model from using the same words or phrases repeatedly, promoting more diverse and varied output.

Function Calling

Function calling is when a program invokes a predefined function to perform a specific task.

Gemini

Collection of multimodal LLMs developed by Google, designed to understand and process various types of data including text, images, audio, video, and code. It is the successor to Google's Bard and represents a significant advancement in Google's generative AI capabilities.

Generative Adversarial Networks (GANs)

Type of deep learning model that consists of two neural networks: a generator and a discriminator. These networks compete against each other to generate new data that resembles the training data, making GANs powerful tools for tasks like image generation, style transfer, and data augmentation.

Generative AI

Generative AI is a type of artificial intelligence that creates new content—like text, images, audio, or video—based on prompts or instructions from users. It learns from large datasets to produce original results that can be helpful in many fields.

Generator

A generator in AI is a component of a generative model that creates new data based on patterns learned from existing data. It's often used in models like Generative Adversarial Networks (GANs) to produce realistic outputs.

Google AI

Artificial intelligence research and development division of Google, focused on advancing AI technologies and integrating them into various Google products and services. It's like the brain behind many of Google's innovative features, driving advancements in machine learning, natural language processing, and more.

GPT (Generative Pre-trained Transformer)

Advanced AI model known for generating text that's almost indistinguishable from human writing. It’s like a robotic author with a knack for mimicking human conversation and composition.

Hackathon

Event where participants, often including prompt engineers, developers, designers, and other specialists, collaborate intensively over a short period, typically 24 to 48 hours, to develop new software, applications, or features. It's a marathon of innovation aimed at solving specific problems or creating new products.

Hugging Face

Popular open-source platform for natural language processing (NLP) and machine learning. It provides pre-trained models, tools, and a community to help developers build and deploy AI models.

Information Architecture (IA)

Information Architecture (IA) is the practice of organizing, structuring, and labeling information to make it easy to find and understand. It creates clear pathways for users to navigate content efficiently and intuitively.

Instruction

Specific directive given to an AI within a prompt. It's like giving your AI assistant a clear, step-by-step recipe to follow, ensuring it knows exactly what you want it to do.

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.

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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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