One of the most buzzed about advances in artificial intelligence recently is the rise of creative generative AI models like DALL-E 2, Stable Diffusion and GPT-3.
These systems can generate shockingly convincing synthetic images, texts, code and more from simple text prompts.
The capability of generative AI seems to improve almost daily. Models can now not only create highly realistic images and passages, but also generate logos, website layouts, infographics, stylized artwork, music and more based on a few descriptive inputs.
This rapid progress excites many about the future potential, but also prompts concerns about how generative models may negatively disrupt industries and societies.
Why is generative AI garnering so much hype and hope now? A few key innovations have unlocked new possibilities:
1. Algorithmic Breakthroughs — Architectures like transformers and diffusion models underpin modern generative AI and have proven extremely adept at building representations from data.
2. Abundant Data — Models are now trained on gigantic labeled datasets scraped from the internet, allowing them to make rich connections between textual concepts and creations.
