Generative AI

Generative artificial intelligence, often called generative AI or GenAI, is a part of artificial intelligence that creates new text, images, videos, audio, software code, and other types of data. It works by learning patterns from large amounts of information and then using those patterns to make something new when given a prompt, which is usually a short piece of text.

Since the 2020s, generative AI has become very popular because of big advances in a type of computer learning called deep neural networks. These advances include something called large language models, which help computers understand and create human-like text. Popular tools include chatbots like ChatGPT, Claude, Copilot, and others, as well as programs that turn text into images like DALL-E and Midjourney, and even ones that create videos.

Businesses in many areas, such as making software, healthcare, finance, entertainment, and art, have started using generative AI to help them work faster and better. However, there are also concerns because these tools can be used to create fake news or deepfakes, and sometimes they learn from materials without permission. They also use a lot of energy and resources, which can affect the environment.

History

Main article: History of artificial intelligence

The story of generative AI begins with early ideas about creating patterns, like the Markov chain. This method, created by mathematician Andrey Markov, helps computers learn and create new text by studying patterns in existing writing.

Later, artists used computers to make art, and new ways to plan and solve problems were developed. In the late 2000s, big changes in computer learning led to better tools for creating images, sounds, and more. Important moments include the release of DALL-E for turning words into pictures, ChatGPT for creating text, and many other tools that made generative AI popular and accessible to everyone.

Applications

Main article: Applications of artificial intelligence

Generative AI is used in many areas to help create new content and automate tasks. In healthcare, it helps find new medicines and create practice data for training diagnostic tools. In finance, it drafts reports, generates data, and automates customer service. The media and entertainment industries use it to compose music, develop scripts, and generate images or videos.

Large language models can process and generate human language and even write computer programs from prompts. They can also create realistic speech and visual art. Generative AI can produce videos, help plan robot movements, and assist in building 3D models from text or images. It can also help discover and improve computer algorithms.

Software and hardware

Generative AI models power tools like chatbot products such as ChatGPT, programming tools such as GitHub Copilot, and text-to-image products such as Midjourney. These features are now found in everyday software like Microsoft Office and Google Photos.

Smaller models can run on devices like smartphones and personal computers, while larger models need powerful laptop or desktop computers with special chips for speed. Very large models often run in big computer centers accessed through the internet.

Law and regulation

Main article: Regulation of artificial intelligence

Different countries have created rules to guide the use of generative AI. In the United States, companies like OpenAI, Alphabet, and Meta agreed to add special marks to show when content is made by AI. They also must share information with the government about certain powerful AI systems.

In the European Union, new rules require companies to tell people when content is created by AI and to share details about the data used to train these systems. In China, rules require AI services to add marks to show when images or videos are made by AI and to follow guidelines about data and values.

Copyright

Main article: Artificial intelligence and copyright

Generative AI learns from many existing works, including those that have copyright protection. Some say this is allowed, while others believe it breaks copyright laws. Courts are still deciding these cases.

The United States Copyright Office says that works made completely by AI without human help cannot be copyrighted. However, they are reviewing these rules to see if they should change for AI. In early 2025, the office allowed the first artwork made entirely by AI to be copyrighted.

Concerns

See also: Ethics of artificial intelligence and Artificial intelligence controversies

The rise of generative AI has sparked many concerns. Leaders and experts worry about how these tools might change jobs, spread false information, or affect society. For example, some people fear that AI could take away jobs in areas like writing, design, and even acting. Others are concerned about the quality of information, as AI can sometimes create incorrect or misleading content.

Generative AI also raises questions about fairness. These tools can sometimes repeat biases found in the data they were trained on, leading to unfair representations of different groups of people. There are also worries about how much energy these AI systems use, as they require a lot of power to train and run.

Detection and awareness

See also: Artificial intelligence content detection

There are tools like GPTZero that can try to find content made by AI, but sometimes they get it wrong and accuse people unfairly (false positives). One way to help detect AI content is through digital watermarking, which changes the content in very small ways that special software can find.

In 2023, OpenAI made a tool for ChatGPT but decided not to share it, fearing people might use other AI instead. In March 2025, the Cyberspace Administration of China said online services must label AI content. Later, in May 2025, Google started using its watermarking tool called SynthID for its AI products. Sadly, in June 2025, some people wrongly thought certain video games used generative AI.