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GAO-24-106946 1 (2024-06-20)

handle is hein.gao/gaoqlx0001 and id is 1 raw text is: Why This Matters Key Takeaways What is generative Al? Use of generative artificial intelligence (Al) has exploded to over 100 million users globally due to recently enhanced capabilities and user interest. This growth has created both excitement and debate about the technology's potential to revolutionize entire industries, such as health care, education, and software engineering. Generative Al technology may dramatically increase productivity and transform daily tasks across much of society. However, it may also displace workers, spread disinformation, and present risks to national security and the environment. For this technology assessment, we were asked to describe generative Al and key aspects of its development. This report is the first in a body of work looking at generative Al. In future reports, we plan to assess best practices and other factors considered for developing and deploying generative Al tools, societal and environmental effects of the use of generative Al, and federal development and adoption of generative Al technologies. To perform this assessment, we conducted literature reviews and interviewed several leading companies developing generative Al technologies. This report provides an overview of how generative Al works, how it differs from other kinds of Al, and examples of its use across various industries. * Generative Al differs from other Al systems in its ability to create novel content, in the vast volumes of data it requires for training, and in the greater size and complexity of its models. * Generative Al systems employ several model architectures, or underlying structures. These systems, referred to as neural networks, are modeled loosely on the human brain and recognize patterns in data. * Commercial developers have created a wide range of generative Al models that produce text, code, image, and video outputs. Developers have also created products and services that enhance existing products or support customized development and refinement of models to meet customer needs. Their benefits and risks are still unclear for many applications. Unlike Al technologies that focus on classification and prediction, generative Al can create content such as text, images, audio, or video when prompted by a user. Generative Al systems create responses that are based on data, often text and images sourced from the internet at large. Users may produce outputs from the software by issuing a query commonly known as a prompt. Many of the generative Al systems now available allow users to prompt the system in natural language. Page 1 GAO-24-1 06946 GENERATIVE ARTIFICIAL INTELLIGENCE Page 1 GAO-24-106946 GENERATIVE ARTIFICIAL INTELLIGENCE