Generative AI Explained: How Models Like GPT-4 and DALL-E Work

Generative AI is a type of artificial intelligence that can create new content, such as text, images, and music. Models like GPT-4 and DALL-E have captured the public's imagination with their ability to generate creative and realistic content. But how do they work?

The Power of Transformers

Most modern generative AI models are based on a neural network architecture called a transformer. A transformer is a type of neural network that is particularly good at understanding the relationships between words in a sentence.

Training on a Massive Dataset

Generative AI models are trained on a massive dataset of text and images. This dataset can include everything from books and articles to websites and social media posts. By training on this massive dataset, the model learns the patterns and relationships in the data.

Predicting the Next Word (or Pixel)

At its core, a generative AI model is a prediction engine. When you give it a prompt, it uses its knowledge of the world to predict the next word (or pixel) in the sequence. It then repeats this process over and over again to generate a complete piece of content.

The Magic of Emergent Abilities

One of the most amazing things about generative AI is that it can develop emergent abilities. These are abilities that were not explicitly programmed into the model, but that emerge from the model's training. For example, a generative AI model might learn how to write a poem, even if it was never explicitly taught how to do so.

The Future of Generative AI

Generative AI is a rapidly developing field, and we are only just beginning to scratch the surface of what is possible. As these models continue to improve, we can expect to see even more amazing and creative applications of generative AI.