What is Generative AI?
Generative AI, a subset of artificial intelligence, includes systems designed to generate images, music, text, and many other forms of media based on its training data. The key is in the name. Rather than analyzing or processing data, generative AI learns from existing data to generate new data that is consistent with the original data set. To do so, those systems have been trained on billions of parameters.
This technology has taken the world by storm due to its wide-ranging potential applications. Large language models (LLMs, a key type of statistical algorithmic approach used in generative AI) can be used to produce textual outputs, such as document summaries, marketing copy, and program code. LLMs can even generate images, video, and other media in response to textual inputs known as prompts. Data and analytics professionals can use LLMs to generate SQL and Python code, sample and synthetic data sets, and visualizations, metrics, summary statistics, and explanations of complex relationships within data sets.
Generative AI introduces issues in data curation, data architecture, governance, intellectual property protection, and other areas of concern to enterprises. Our research team and contributing authors address many of these topics in their reports and webinars; see the resources linked below, or start by reading this overview, Generative AI and Its Implications for Data and Analytics.