Text in Image: Glossary Of Terms

Glossary of AI Text Generation Terms: Best 19

A brief glossary of terms related to AI text generation:

Are you a newcomer to the world of AI generated text?

Don’t worry, you’ve come to the right place! This page provides a brief glossary of AI text generation terms (Artificial Intelligence). Get an insight into the AI tech involved with AI text creation, and understand some of the features of various applications.

You can click through to read more detail on each topic.


Artificial intelligence (AI) is the ability of a computer or machine to perform tasks that would typically require human intelligence, such as learning, problem-solving, and decision making. There are many different types of AI, ranging from simple rule-based systems to more advanced machine learning algorithms that can learn and adapt on their own.

Natural Language Processing (NLP):

Natural Language Processing (NLP) is a branch of Artificial Intelligence (AI) that deals with understanding and generating natural language for tasks such as text classification, sentiment analysis, information extraction, document summarization, and machine translation. In NLP, a computer processes human language to interpret the meaning behind it, identify and distinguish key concepts, and uncover complicated relationships between them. NLP relies on machine learning algorithms to identify structures, relations, and other elements in natural language.

Machine Learning:

Machine learning is a type of artificial intelligence that allows computers to learn and improve their performance on a specific task without being explicitly programmed. It involves feeding a computer a large amount of data and using algorithms to analyze and recognize patterns within that data. The computer can then use these patterns to make predictions or decisions about new data it has not seen before.

For example, a machine learning model might be trained to recognize objects in images by analyzing thousands of labeled images of those objects. The model would learn to identify the characteristics that are common among the objects and use that knowledge to classify new images as containing those objects or not.

Neural Network:

Neural networks, also called ANNs or SNNs, are a type of machine learning. They are inspired by how the human brain works and use a network of nodes, or artificial neurons, to process data. Each node has an associated weight and threshold. When the output of a node is above the threshold value, it sends data to the next layer of the network. Otherwise, no data is sent. ANNs have an input layer, one or more hidden layers, and an output layer. They are used to create deep learning algorithms.

Language Model:

A language model is a statistical model that is used to predict the likelihood of a sequence of words or tokens in a given language. Language models are commonly used in natural language processing (NLP) tasks, such as speech recognition, machine translation, and text generation.

Text Generation:

Text generation is the process of creating written text automatically using artificial intelligence (AI) algorithms and models. This can be done through the use of natural language processing (NLP) techniques, which allow the AI system to understand and generate human-like text. Text generation can be used for a variety of purposes, such as generating summaries of long-form content, creating automated responses or customer service messages, or generating personalized content for social media or other platforms.

Personalized AI Avatar:

A personalized avatar is an AI-generated image that digitally displays a representation of a person. This representation is built based on a set of defining characteristics that have been customized to represent the individual user.

The attributes used to personalize the avatar often include the person’s age, gender, physical appearance, hairstyle, clothing and other features. Depending on the type of personalized avatar, additional customization features may include changing emotions, poses or facial expressions.

Personalized avatars can be used to create virtual assistants for online chat and customer support. They can also be used as virtual guides for online tutorials, as well as for gaming, education and entertainment. Personalized avatars can even be used to represent a user on several digital platforms. By creating one avatar to use across many platforms, the user can maintain their digital identity while remaining anonymous.

Text Prompt:

In the context of artificial intelligence (AI), a text prompt is a piece of written text that is used to stimulate or guide the AI system’s thinking or output. Text prompts can be used to train AI models or to generate responses or output from the AI system. For example, a text prompt might be used to teach an AI model how to recognize and classify different types of text, such as spam emails or news articles. A text prompt might also be used to generate responses from an AI chatbot or virtual assistant, such as by providing a question or request for the AI system to respond to.


GPT-3 is an unsupervised large-scale language model developed by OpenAI, a research organization dedicated to artificial intelligence (AI). GPT-3 uses transformer, a deep learning technology that can store and process massive amounts of data, to learn and generate language.

It is trained on a large dataset of text and can generate natural-sounding human-like sentences and paragraphs based on a prompt. GPT-3 can be used to create text-based applications like chatbots, automated summarization systems, and text generators. In addition, GPT-3 can help with such tasks as text classification, question answering, natural language understanding, and natural language generation.


OpenAI is an artificial intelligence (AI) research and deployment company with a mission to ensure that artificial general intelligence (AGI) benefits all of humanity. The company aims to directly build safe and beneficial AGI, but also considers its mission fulfilled if its work helps others achieve this outcome.

OpenAI has achieved several milestones in its work, including DALL·E 2, GTP-3, ChatGPT-3, and the OpenAI Codex API. The company is governed by a board of directors, including employees and non-employees, and is funded by investors such as Microsoft and Khosla Ventures. OpenAI was founded by Sam Altman, Ilya Sutskever, Greg Brockman, Wojciech Zaremba, Elon Musk, and John Schulman and is currently based in San Francisco.


Dall-E (Dual-stage Attentive Language Representation) is an AI language model developed by OpenAI, a research laboratory specializing in artificial intelligence. This language model uses deep learning to understand natural language and generate images from text descriptions. It utilizes a dual-stage attention mechanism, a sequence-to-sequence architecture, and transfer learning to generate high-quality images.

The model can read and understand natural language prompts, such as “a happy puppy riding a skateboard,” and produce a corresponding real-world image. Dall-E is the first large-scale AI system capable of creating and understanding “creative language” and has been used for a variety of applications such as image and video generation.

Text to Speech:

Text to speech (TTS) is a process of generating synthetic, computer-generated speech from a text source using artificial intelligence. It converts written text into a sequence of phonemes, which are then used to produce spoken words. Such speech can be used in applications such as voice assistants, customer service bots, digital books, and audio narration.

Text to Video:

Text to video (T2V) is a process that employs Artificial Intelligence (AI) algorithms and models to generate videos from text and other data sources. This AI-based technology helps to translate text input prompts into animated videos. A number of elements such as text, audio, and visuals can be combined to create a video.

Text to Art:

Text to Art is a process of creating art from text that leverages Artificial Intelligence (AI) algorithms and models to interpret text and create art pieces with digital tools. Through this process, text, such as words or short phrases, is used as an input to generate images or patterns. The resulting images can then be used to create physical objects such as prints on canvas, 3D printed items, and others.

Text to Pokemon:

Text to Pokemon is an AI-based process that uses algorithms and models to transcribe a given text into a 3D Pokemon character. This technology can be used to produce creative interactive content such as personal avatars, games, and animations. It works by taking textual input such as a name or phrase, and translating it into a 3D virtual character in the style of a Pokemon.

Text to Adventure:

Text to adventure is a process of using AI algorithms and models to create text-based adventure games. By employing Natural Language Processing (NLP) technologies to parse and interpret text, algorithms can be used to create players, environment, non-player characters (NPCs), objects, and text-driven plots and storylines

Text-to-Image Synthesis:

This refers to the same process of generating images based on a given text prompt using AI algorithms and models shown below as Text to Image

Text to Image:

Text to image (T2I) involves taking a piece of text as the input and generating an image based on the content of the text. AI algorithms and models are used to translate the textual information into a visual representation. These algorithms learn from large amounts of data and example images to convert text into images with almost realistic and often varied output.