book chapter · Apress eBooks · 2024

Hardware Optimization for Generative AI

Cited by 0Abstract and details only

Abstract

The field of generative artificial intelligence (AI) has emerged as one of the most exciting yet computationally demanding areas within AI research today. Generative models, such as large language models, possess the remarkable ability to generate human-like text, images, video, and more, leading to a wide range of beneficial applications. However, the training and operation of these complex neural network models require immense amounts of computing power, which poses a significant challenge.

Cite this paper

APA 7

Dua, I. K., & Patel, P. (2024). Hardware Optimization for Generative AI. Apress eBooks, 57–84. https://doi.org/10.1007/979-8-8688-0917-0_3

MLA 9

Dua, Ishneet Kaur, and Pretesh Patel. “Hardware Optimization for Generative AI.” Apress eBooks, 2024, pp. 57–84, https://doi.org/10.1007/979-8-8688-0917-0_3.

Chicago

Dua, Ishneet Kaur, and Pretesh Patel. 2024. “Hardware Optimization for Generative AI.” Apress eBooks: 57–84. https://doi.org/10.1007/979-8-8688-0917-0_3.

Harvard

Dua, I.K. and Patel, P. (2024) ‘Hardware Optimization for Generative AI’, Apress eBooks, pp. 57–84. Available at: https://doi.org/10.1007/979-8-8688-0917-0_3.

BibTeX

@incollection{dua2024hardware,
  title = {{Hardware Optimization for Generative AI}},
  author = {Dua, Ishneet Kaur and Patel, Pretesh},
  booktitle = {Apress eBooks},
  pages = {57--84},
  year = {2024},
  doi = {10.1007/979-8-8688-0917-0_3}
}

Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.