Generative AI offers both upsides and downsides to early adopters. In this case, the upsides include rich digital interactions and a healthy productivity boost. The downsides, however, range from confused customers to operational errors and privacy breaches.

GenAI refers to a type of artificial intelligence that generates digital content such as text, images, or audio after being trained on a corpus of existing content. The most broadly applicable form of GenAI centers on a language model (LM), which is a type of neural network whose interconnected nodes collaborate to interpret, summarize, and generate text.

Generative AI (GenAI) is a type of neural network that trains itself to interpret and create digital content such as text, images, or audio. GenAI first gained prominence in 2014 with the rise of generative adversarial networks (GANs), in which one neural network iteratively approves or rejects synthetic content from another network. (For example, GANs create “deep fake” videos.) In 2017, researchers at Google introduced a “transformer” architecture that converts sequences of inputs into sequences of outputs, giving rise to the large language model (LLM.)