CREATIVE GENERATIVE AI

Generative AI vs. other types of AI.

Discover the different types of artificial intelligence (AI), how they compare to generative AI, and how Adobe uses generative AI in Adobe Creative Cloud apps

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Firefly generated castle on coastal rocks illustrating differences between generative AI vs other AI types

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The three types of AI

Where generative AI fits in

The types of generative AI

Adobe and the future of generative AI

Al has always been on our minds.

For centuries humans have conceived of artificial intelligence in mythology and fiction. From Talos, the giant bronze automaton (self-operating machine) that protected the island of Crete in Greek mythology, to the spacecraft-controlling HAL in 2001: A Space Odyssey, our imaginations have been captured by the idea of intelligent machines created by humans.

Now AI technology is part of everyday life, analyzing data, making predictions, and boosting productivity. Most recently, in the form of generative AI, it’s helping us create art.

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What is artificial intelligence?

Artificial intelligence is the simulation of human intelligence by a machine. Despite ancient mythologizing and centuries of efforts to create machines that could act like humans, the first true example of machine learning came in 1951 when a checkers program at the University of Manchester learned how to play well enough to beat human players. This was the earliest form of game AI.

Today, AI is everywhere, especially in our phones and mobile apps, where it performs common tasks like facial recognition, speech recognition, spam filtering, grammar suggestions, and language translation.

The three types of AI.

There isn’t a single type of AI that does everything. Just as we use different computer programs for word processing, accounting, and digital compositing, there are different types of AI that work differently to achieve different goals. The types of AI that you’re likely to encounter on any given day fall into three basic categories.

Narrow AI

This type of AI performs specific tasks and doesn’t learn beyond that. Image recognition, natural language processors, and image generators are forms of narrow artificial intelligence. Siri, Google Assistant, and Alexa are forms of narrow AI. They can understand and respond to voice commands, but they can’t give you accurate medical diagnoses.

Reactive machines

As the name suggests, these machines can only react to stimuli, like the movement of a chess piece on virtual chessboard. They don’t build memories that they can retrieve in the future like limited memory AI machines, but they’re useful parts of digital life. Spam filters and recommender systems that note your behavior and suggest what you should watch next or what you might like to buy are reactive machines.

Limited memory AI

The next step in AI development after reactive machines, limited memory AI can store knowledge, learn from it, and perform new tasks based on that learning. This type of AI is useful for making predictions, and it’s used to forecast future trends in everything from finance to the weather. This is the most common type of AI in use today, appearing in chatbots and self-driving cars.

Building covered with plants and moss showing application of text prompts with generative AI vs other AI

Where generative AI fits in.

Generative AI is a subset of narrow AI, but it offers a broad range of possibilities for creators of all kinds of content. Trained on enormous datasets, generative AI recognizes patterns in that data and draws conclusions about what it’s learned. Then it can take a text description and apply that machine learning to create new patterns and produce something new.

Part of what makes generative AI so exciting is how easy it is to use. By typing a simple text prompt into a field, you can get near-immediate results. Plus, there are so many ways generative AI can help with tasks big and small.

Web developers use it to fix bugs in computer code. Companies use it for customer service chatbots. Scientists use it for diagnostics and research. Teachers, writers, artists, and musicians all use it to brainstorm and quickly try out new ideas.

Learn more about how generative AI works

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Types of generative AI.

Just as other subsets of AI are built for specific purposes, generative AI includes different types of models built to produce different types of content.

Text generation

Text generation is perhaps the most talked about form of AI, and chatbot AI models have become popular and appear in the news regularly. People use these text generators for everything from proofreading to writing surveys to creating code.

Image generation

AI generators like Adobe Firefly can turn a text prompt into an image. They have a wide range of uses for artists, content creators, and marketers. Trained on hundreds of millions of images and captions, AI image generators give anyone the power to describe what they want and quickly generate a new image based on a text description.

Artists and designers can use this technology to brainstorm new ideas and try new ways of imagining their work without devoting hours to each iteration. Marketers and independent content creators can produce beautiful images quickly even if they aren’t experienced artists. With great text prompts, AI generated art, photorealistic images, and even paintings can be created.

Sound generation

Just as image generators are trained on huge datasets of images, AI music generators are trained on music and metadata. They can identify patterns in music genres and the work of specific artists and create new music based on those characteristics.

Video generation

This form of generative AI combines all three forms of video, sound, and image generation. An AI video generator is trained on data that includes audio, video, and text. These models can help video producers save time editing, adding captions, resizing for different outputs, and even generating new video content based on text to video prompts.

Kangaroo skydiving in ultra HD resolution showing use case of generative AI vs other AI

Text-to-image prompt: ultra hd, a kangaroo skydiving

Adobe and the future of generative AI.

Right now you can use Adobe Firefly as an AI image generator to turn text into images, create text effects, add or subtract elements in your own images, and create new color variations in vector artwork. But Firefly is also embedded in Adobe Creative Cloud apps like Photoshop and Illustrator, giving creators the power to transform their images quickly and then use precision tools that have been around for years to make generated content fit seamlessly with their own.

Soon you may be able to generate custom vectors, brushes, and textures from text prompts, change the weather in a video with a few words, or turn a 3D design into a photorealistic image. With existing features and those to come, creators of all abilities will be able to expand on their natural creativity and bring any vision to life.

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