artificial intelligence model capable of generating content in response to a prompt
Wikipedia
en.wikipedia.org › wiki › Generative_artificial_intelligence
Generative artificial intelligence - Wikipedia
1 day ago - Generative artificial intelligence (Generative AI, GenAI, or GAI) is a subfield of artificial intelligence that uses generative models to generate text, images, videos, audio, software code or other forms of data.
Google Cloud
cloud.google.com › use-cases › generative-ai
What is Generative AI? Examples & Use Cases | Google Cloud
Generative AI can be used to: - Improve customer interactions through enhanced chat and search experiences · - Explore vast amounts of unstructured data through conversational interfaces and summarizations · - Assist with repetitive tasks ...
What is generative AI and how does it work?
Generative AI is a type of artificial intelligence that can create new content, such as text, images, music, audio, and videos, using generative models. Generative models are machine learning models that learn the patterns and structure of a given dataset and then generate new data that has similar characteristics. For example, a generative model trained on a dataset of human faces can generate new faces that look realistic but do not belong to any real person. There are different types of generative models, such as variational autoencoders (VAEs), generative adversarial networks (GANs), autoregressive models, and transformers. Each of these models has its own advantages and disadvantages, depending on the task and the data. For instance, GANs are good at producing high-quality images, but they are difficult to train and prone to mode collapse. Transformers are good at generating natural language, but they require a lot of computational resources and data. Generative AI has many applications in creative activities, data enrichment, problem-solving, and more. For example, generative AI can be used to synthesize new images for art or entertainment, augment existing data for training or testing purposes, solve complex optimization problems, or generate novel ideas or solutions. More on reddit.com
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October 12, 2023What is Generative AI?
Yo dawg, I heard you like generative AI, so I got a generative AI to write about generative AI, so you can generative AI while you generative AI. More on reddit.com
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August 6, 2024What's the point of generative AI?
Some people like it, it's clear that you don't. Some people like mustard, I hate it. I understand that other people like what i don't, and i don't get bothered by it. It's okay. More on reddit.com
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June 1, 2025Here's my non-technical guide to Generative AI basics (Part 1)
YES PLEASE!! Part 2 More on reddit.com
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January 28, 2025Videos
14:16
Generative AI in Business: 5 Use Cases - YouTube
06:19
Generative AI: what is it good for? - YouTube
Introduction to Generative AI
Generative AI Explained In 5 Minutes | What Is GenAI ...
21:30
Generative AI Examples | The Best Real-World Examples of Generative ...
Generative AI explained in 2 minutes
University Center for Teaching and Learning
teaching.pitt.edu › resources › what-is-generative-ai
What is Generative AI? – University Center for Teaching and Learning
Generative artificial intelligence (AI) tools use machine learning models trained on massive pools of information to learn patterns from data to create novel content like text, images, audio, or video in response to a prompt. Unlike internet searches, generative AI tools do not use algorithms ...
AWS
aws.amazon.com › what is cloud computing › cloud computing concepts hub › generative ai
What is Generative AI? - Gen AI Explained - AWS
1 week ago - Generative artificial intelligence (generative AI) is a type of AI that can create new content and ideas, including conversations, stories, images, videos, and music. It can learn human language, programming languages, art, chemistry, biology, or any complex subject matter.
IBM
ibm.com › think › topics › generative-ai
What is Generative AI? | IBM
5 days ago - Generative AI relies on sophisticated machine learning models called deep learning models algorithms that simulate the learning and decision-making processes of the human brain. These models work by identifying and encoding the patterns and relationships in huge amounts of data, and then using that information to understand users' natural language requests or questions and respond with relevant new content. AI has been a hot technology topic for ...
McKinsey
mckinsey.com › featured-insights › mckinsey-explainers › what-is-generative-ai
What is ChatGPT, DALL-E, and generative AI? | McKinsey
April 2, 2024 - Until recently, machine learning ... models, used to observe and classify patterns in content. For example, a classic machine learning problem is to start with an image or several images of, say, adorable cats. The program would then identify patterns among the images, and then scrutinize random images for ones that would match the adorable cat pattern. Generative AI was a ...
NVIDIA
nvidia.com › generative ai
What is Generative AI and How Does it Work? | NVIDIA Glossary
Generative AI models use neural networks to identify the patterns and structures within existing data to generate new and original content. One of the breakthroughs with generative AI models is the ability to leverage different learning approaches, ...
Reddit
reddit.com › r/generativeai › what is generative ai and how does it work?
r/generativeAI on Reddit: What is generative AI and how does it work?
October 12, 2023 -
I'm a student trying to learn about AI for my Information systems class. I hope we can have an informed discussion. I want to start this discussion off with a basic question. There is no need to have extensive or professional knowledge on the subject, enthusiasts are welcome!
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Generative AI is a type of artificial intelligence that can create new content, such as text, images, music, audio, and videos, using generative models. Generative models are machine learning models that learn the patterns and structure of a given dataset and then generate new data that has similar characteristics. For example, a generative model trained on a dataset of human faces can generate new faces that look realistic but do not belong to any real person. There are different types of generative models, such as variational autoencoders (VAEs), generative adversarial networks (GANs), autoregressive models, and transformers. Each of these models has its own advantages and disadvantages, depending on the task and the data. For instance, GANs are good at producing high-quality images, but they are difficult to train and prone to mode collapse. Transformers are good at generating natural language, but they require a lot of computational resources and data. Generative AI has many applications in creative activities, data enrichment, problem-solving, and more. For example, generative AI can be used to synthesize new images for art or entertainment, augment existing data for training or testing purposes, solve complex optimization problems, or generate novel ideas or solutions.
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Generative AI (GAI) is the name given to a subset of AI machine learning technologies that have recently developed the ability to rapidly create content in response to text prompts, which can range from short and simple to very long and complex. Different generative AI tools can produce new audio, image, and video content, but it is text-oriented conversational AI that has fired imaginations. In effect, people can converse with, and learn from, text-trained generative AI models in pretty much the same way they do with humans. Businesses large and small should be excited about generative AI’s potential to bring the benefits of technology automation to knowledge work, which until now has largely resisted automation. Generative AI tools change the calculus of knowledge work automation; their ability to produce human-like writing, images, audio, or video in response to plain-English text prompts means that they can collaborate with human partners to generate content that represents practical work. How Does Generative AI work? There are two answers to the question of how generative AI models work. Empirically, we know how they work in detail because humans designed their various neural network implementations to do exactly what they do, iterating those designs over decades to make them better and better. AI developers know exactly how the neurons are connected; they engineered each model’s training process. Yet, in practice, no one knows exactly how generative AI models do what they do—that’s the embarrassing truth. “We don’t know how they do the actual creative task because what goes on inside the neural network layers is way too complex for us to decipher, at least today,” said Dean Thompson, a former chief technology officer of multiple AI startups that have been acquired over the years by companies, including LinkedIn and Yelp, where he remains as a senior software engineer working on large language models (LLMs). Generative AI’s ability to produce new original content appears to be an emergent property of what is known, that is, their structure and training. So, while there is plenty to explain vis-a-vis what we know, what a model such as GPT-3.5 is actually doing internally—what it’s thinking, if you will—has yet to be figured out. Some AI researchers are confident that this will become known in the next 5 to 10 years; others are unsure it will ever be fully understood. Here’s an overview of what we do know about how generative AI works: • Start with the brain. To improve its predictive ability, the brain builds an internal representation of the world. In his theory, human intelligence emerges from that process. Whether influenced by Hawkins or not, generative AI works exactly this way. And, startlingly, it acts as if it is intelligent. • Build an artificial neural network. All generative AI models begin with an artificial neural network encoded in software. Thompson says a good visual metaphor for a neural network is to imagine the familiar spreadsheet, but in three dimensions because the artificial neurons are stacked in layers, similar to how real neurons are stacked in the brain. Each layer may have tens, hundreds, or thousands of artificial neurons, but the number of neurons is not what AI researchers focus on. Instead, they measure models by the number of connections between neurons. The strengths of these connections vary based on their cell equations’ coefficients, which are more generally called “weights” or “parameters.” These connection-defining coefficients are what’s being referred to when you read, for example, that the GPT-3 model has 175 billion parameters. The latest version, GPT-4, is rumored to have trillions of parameters, though that is unconfirmed. There are a handful of neural network architectures with differing characteristics that lend themselves to producing content in a particular modality; the transformer architecture appears to be best for large language models, for example. • Teach the newborn neural network model. Large language models are given enormous volumes of text to process and tasked to make simple predictions, such as the next word in a sequence or the correct order of a set of sentences. In practice, though, neural network models work in units called tokens, not words.
MIT News
news.mit.edu › 2023 › explained-generative-ai-1109
Explained: Generative AI | MIT News | Massachusetts Institute of Technology
A generative AI system is one that learns to generate more objects that look like the data it was trained on. “When it comes to the actual machinery underlying generative AI and other types of AI, the distinctions can be a little bit blurry.
Accenture
accenture.com › us-en › insights › generative-ai
What is Generative AI & Why is It Important? | Accenture
Generative AI uses natural language processing (NLP), machine learning (ML) and image recognition to respond to prompts autonomously, mimicking human cognition to solve problems while evolving over time.
Harvard University Information Technology
huit.harvard.edu › ai
Generative Artificial Intelligence (AI) | Harvard University Information Technology
Generative AI is a type of artificial intelligence that can learn from and mimic large amounts of data to create content such as text, images, music, videos, code, and more, based on inputs or prompts.
Coursera
coursera.org › coursera articles › data › ai and machine learning › what is generative ai? how it works, examples, benefits, and limitations
What Is Generative AI? How It Works, Examples, Benefits, and Limitations | Coursera
August 15, 2025 - Generative AI is a type of artificial intelligence tool that generates images, text, videos, and other media in response to inputted prompts from a user. AI generators, like ChatGPT and DALL-E, have become popular for their ability to handle ...
Gartner
gartner.com › en › topics › generative-ai
Enterprise Guide to Generative AI: Expert Insights on ROI, Use Cases, and Cost Management
September 24, 2025 - Gartner clients lean on our AI Use Case Insights to explore, evaluate and prioritize 1,000+ proven AI use cases and real-world case studies tailored to their industries. These are a sampling: ... Use case: Automated content generation for marketing materials, social media posts and personalized customer communications
SAP
sap.com › products › artificial-intelligence › what-is-generative-ai.html
What is Generative AI? | Examples, Use Cases | SAP
Generative AI is a form of artificial intelligence that can produce text, images, and varied content based on the data it is trained on. ... Generative AI refers to artificial intelligence models designed to generate new content in the form ...
Coursera
coursera.org › coursera articles › data › ai and machine learning › 20 examples of generative ai applications across industries
20 Examples of Generative AI Applications Across Industries | Coursera
June 3, 2025 - In this article, you’ll learn ... Generative AI is artificial intelligence designed to create unique text or image results in response to user prompts....
Quantiphi
quantiphi.com › blog › generative-ai
Generative AI: Applications, Use Cases, and Examples | Quantiphi - Quantiphi
Learn about Generative AI, its applications, use cases, examples, and more to understand how it can enhance productivity across different industries.
Cornell Teaching
teaching.cornell.edu › generative-artificial-intelligence
Generative Artificial Intelligence | Center for Teaching Innovation
Generative artificial intelligence is a subset of AI that utilizes machine learning models to create new, original content, such as images, text, or music, based on patterns and structures learned from existing data. A prominent model type used by generative AI is the large language model (LLM).
Oracle
oracle.com › cloud › artificial intelligence › generative ai
What is Generative AI? How Does It Work?
February 11, 2025 - Generative AI became a viral sensation in November 2022 and is expected to soon add trillions of dollars to the global economy—annually. AI is a form of neural network–based machine learning trained on vast data sets that can create novel text, image, video, or audio content in response to users’ natural language prompts.
Harvard University Information Technology
huit.harvard.edu › news › ai-use-cases
Ideas for experimenting with Generative AI: Use cases and things to keep in mind | Harvard University Information Technology
AI can create stories, poems, music, images, recipes, travel guides, study guides, lesson plans, surveys and much more in seconds from simple, natural language prompts. It can generate new ideas or help you get creatively unstuck.
MIT Sloan
mitsloan.mit.edu › ideas-made-to-matter › machine-learning-and-generative-ai-what-are-they-good-for
Machine learning and generative AI: What are they good for in 2025? | MIT Sloan
June 2, 2025 - In addition to its main function, which is generating new content, generative AI is taking over tasks that traditional machine learning has historically performed. These situations include: When you’re dealing with everyday language or common ...