Why Everyone Is Talking About Generative AI, Not Just The Experts
VentureBeat, April 17th, 2023
Improvements over the last decade in machines' ability to generate images and text have been staggering. As is often the case with innovation, progress is not linear, but comes in leaps and bounds, which surprises and delights researchers and users alike. 2022 was a banner year for innovation in generative AI, built on the advent of diffusion methods for image generation and of increasingly large-scale transformers for text generation.
And while it provided a major leap forward for the entire natural language processing (NLP) industry, there are three reasons why generative AI models were the first to stir the public's excitement, and why they'll still be the main points of entry into what language AI can do for the time being.