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 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 instruction following that 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.
Certain generative AI models, such as those underlying Stable Diffusion, Midjourney, and DALL-E, can produce, extend, or refine images from prompts.
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 the 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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