What is Generative AI?
Generative AI produces content, including text, images, music, and computer code. A request might produce a first draft of a letter, an illustration, or a proposed software function. The output gives a person something to examine and revise.
Think of a writer preparing several drafts from the same brief. A generative model can offer different versions, drawing on patterns learned during training. You still have to decide whether any of them serves the purpose.
How Does Generative AI Work?
At its core, Generative AI operates using algorithms that are able to learn from a set of data and then generate new data similar to the original set. These algorithms are a part of machine learning models called Generative models, like Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs).
One of the most recognizable applications of Generative AI is the training of a model on a dataset of images. After learning from this dataset, the model can generate new images that bear a remarkable similarity to the originals, while being entirely unique creations.
Real-world Applications of Generative AI
Generative AI isn't just a theoretical concept – it has practical applications across a wide range of industries. Here are some generative AI examples:
- Art and Design: Generative AI can create unique pieces of art or design objects, such as furniture or home decor, by learning from existing styles and trends. These tools are used for what can be conceptualized as AI assisted painting. Examples of AI that is designed to generate art and design include OpenAI Dall-E and Midjourney free. With these tools AI artists online are giving generative AI meaning.
- Writing and Journalism: Generative AI can help draft articles, blog posts, or reports, producing a first pass that human writers can check, refine, and polish. A useful starting prompt specifies the audience, purpose, source material, and desired length.
- Music and Entertainment: Generative AI algorithms can create new pieces of music or script dialogues for a movie, offering a new tool for musicians and filmmakers.
- Healthcare and Medicine: Generative AI applications include producing synthetic patient data for research and proposing molecules for drug discovery.
The Future of Generative AI
The useful question is what a generated result contributes to the work. Does it save drafting time? Offer an idea worth developing? Introduce errors that take longer to correct? Those comparisons help determine where generative AI is worth using.
The guides on this site explain prompts, context windows, and other concepts that help you make those comparisons.
