In a talk from the cutting edge of technology, OpenAI cofounder Greg Brockman explores the underlying design principles of ChatGPT and demos some mind-blowing, unreleased plug-ins for the chatbot that sent shockwaves across the world. After the talk, head of TED Chris Anderson joins Brockman to dig into the timeline of ChatGPT's development and get Brockman's take on the risks, raised by many in the tech industry and beyond, of releasing such a powerful tool into the world. The Inside Story of ChatGPT's Astonishing Potential by Greg Brockman is licensed CC-BY-NC-ND4.0 International.
Generative AI, short for Generative Artificial Intelligence, refers to a class of artificial intelligence algorithms and models that can generate new content, such as images, text, music, videos, and more, that is similar to the data it was trained on. Unlike traditional AI systems that are designed to recognize patterns or make decisions based on existing data, generative AI is capable of creating new data from scratch.
One of the fundamental techniques used in generative AI is the generative model, which is a type of machine learning model that learns to model the underlying distribution of the training data. These models are trained on large datasets and learn the patterns and features within that data in order to generate new data points that resemble the original data.
Generative AI has found applications in various fields, such as creative content generation, data augmentation for training other AI models, generating realistic images for computer graphics, and even assisting in drug discovery through molecule generation.
However, it's essential to note that with the power to generate realistic content, generative AI also raises concerns about potential misuse, such as deepfake generation and fake news propagation. As the technology advances, ethical considerations and responsible use become critical to harness its benefits responsibly.