What is generative AI?

Generative AI is the process of AI algorithms generating or creating an output, such as text, photo, video, code, data, and 3D renderings, from data they are trained on. 

The purpose of generative AI is to create content, as opposed to other forms of AI, which might be used for other purposes, such as analyzing data or helping to control a self-driving car.

Why is generative AI a hot topic right now?

The term generative AI is causing a buzz because of the increasing popularity of generative AI programs, such as OpenAI’s ChatGPT and DALL-E. The conversational chatbot and AI image generator both use generative AI to produce new content, including computer code, essays, emails, social media captions, images, poems, excel formulas, and more within seconds, drawing in people’s attention.  

ChatGPT has become extremely popular, accumulating more than one million users a week after launching. Many other companies have also rushed in to compete in the generative AI space, including Google, Microsoft’s Bing, and Opera. The buzz around generative AI is sure to keep on growing as more companies join in and find new use cases.

What does machine learning have to do with generative AI?

Machine learning refers to the subsection of AI that teaches a system to make a prediction based on data it’s trained on. An example of this kind of prediction is when DALL-E is able to create an image based on the prompt you enter by discerning what the prompt actually means. Generative AI is, therefore, a machine-learning framework. 

What systems use generative AI?

Generative AI is used in any algorithm/model that utilizes AI to output a brand new attribute. Right now, the most prominent examples are ChatGPT and DALL-E. 

Another example is MusicLM, Google’s unreleased AI text-to-music generator. An additional contender (which hasn’t performed as well as ChatGPT) is Google’s Bard.

What is generative AI art?

Generative AI art is created by AI models that are trained on existing art. The model is trained on billions of images found across the internet. The model uses this data to learn styles of pictures and then uses this insight to generate new art when prompted by an individual through text.

A popular example of an AI art generator is DALL-E. However, there are plenty of other AI generators on the market that are just as capable and suit different needs. Google has an unreleased AI art generator called Imagen that is still in the research stage.

What are text based generative AI models trained on?

Recent text based models, such as ChatGPT, are trained by being given massive amounts of text in a process known as self-supervised learning. In these cases, the model learns from the information it was fed to then make predictions and provide answers in the future.