What is Generative AI? AI systems that can generate new content based on a variety of inputs. Inputs and outputs to these models can include text, images, audio, 3D models, or other types of data. Large Language Models (LLMs) such as GPT-4 and Llama 2 are popular examples of Generative AI. How Does Generative AI Work? Generative AI models employ neural networks to identify patterns and structures in existing data, enabling them to generate new and original content. A notable breakthrough in generative AI is the ability to apply various learning approaches, including unsupervised or semi-supervised learning, in their training. This has empowered organizations to more effectively and rapidly utilize large volumes of unlabeled data to create foundational models. These models, as their name suggests, serve as a base for AI systems capable of performing multiple tasks. Examples of these foundational models include GPT-4 and Stable Diffusion, which enhance the user's ability to harness the nuances of language. For instance, applications such as ChatGPT, powered by GPT-4, allow users to generate essays from short text prompts. In contrast, Stable Diffusion can create photorealistic images based on text inputs. In the next video we will dive deeper into Large Language Models. Stay tuned!