Generative AI is a category of AI that excels at creating new content after learning patterns in real-world data. When provided with inputs or prompts, various generative AI models can generate diverse types of content. Here are some examples:
Text Generation Models: Text generation models that have been aligned—typically through Reinforcement Learning from Human Feedback—include OpenAI ChatGPT, Google PaLM 2, and Meta LLaMA-2-Chat. These models are capable of unprecedented (albeit imperfect) capabilities in instruction following, which has led to their adoption across many industries. Particularly surprising are their abilities to perform zero-shot and few-shot learning, language translation, programming, and fluently generating meaningful content across a vast number of domains.
Text-to-Image Models: Certain generative AI models, such as those underlying Stable Diffusion, Midjourney, and DALL-E, can produce, extend, or refine images from prompts.
Text-to-Video Generation: Other models like Meta’s Make-A-Video can generate videos from prompts as well.
AI models with generative capabilities, e.g., ChatGPT, DALL-E, etc., are also referred to by regulators as ‘general-purpose AI’ or ‘foundation models’. These AI models are trained on large sets of unlabelled data that can be used for different tasks with minimal fine-tuning.
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