Foundation and large language models: fundamentals, challenges, opportunities, and social impacts

• Published in: Cluster computing Vol. 27; no. 1; pp. 1 - 26
• Main Authors: Myers, Devon, Mohawesh, Rami, Chellaboina, Venkata Ishwarya, Sathvik, Anantha Lakshmi, Venkatesh, Praveen, Ho, Yi-Hui, Henshaw, Hanna, Alhawawreh, Muna, Berdik, David, Jararweh, Yaser
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.02.2024; Springer Nature B.V
• Subjects: Adaptation; Artificial intelligence; Chatbots; Computer Communication Networks; Computer Science; Computers; Industrial development; Language; Large language models; Machine translation; Natural language processing; Neural networks; Operating Systems; Processor Architectures; Advanced pre-trained models; Natural language processing; Foundation models; Large language models; Artificial intelligence; Machine learning

Foundation and Large Language Models (FLLMs) are models that are trained using a massive amount of data with the intent to perform a variety of downstream tasks. FLLMs are very promising drivers for different domains, such as Natural Language Processing (NLP) and other AI-related applications. These...