ASEE PEER - Leveraging the power of multi-modal AI technologies to build and scale generative AI applications
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Leveraging the power of multi-modal AI technologies to build and scale generative AI applications

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Conference

2024 ASEE PSW Conference

Location

Las Vegas, Nevada

Publication Date

April 18, 2024

Start Date

April 18, 2024

End Date

April 20, 2024

DOI

10.18260/1-2--46051

Permanent URL

https://peer.asee.org/46051

Paper Authors

biography

Mohammad Rafiq Muqri DeVry University, Pomona

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Dr. Mohammad R. Muqri is a Professor in College of Engineering and Information Sciences at DeVry University. He received his M.S.E.E. degree from University of Tennessee, Knoxville. His research interests include machine learning, deep learning and generative AI applications

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Abstract

The objective of this paper is to bring awareness, instigate interest, and promote the need of using generative AI tools for information and engineering technology students. Generative artificial intelligence (AI) is a form of AI that can autonomously generate new content, such as text, images, audio, and video. This paper will also attempt to review some of the widely used platforms for generative AI like Amazon Bedrock, Chat Generative Pre-trained Transformer (ChatGPT), and Character.AI . It will expose students to multi-modal AI technologies and help them to analyze, interpret, and generate information in greater detail by leveraging different perceptual modes and guide them to help explore the benefits, features, typical use cases, and technical concepts behind them.

Muqri, M. R. (2024, April), Leveraging the power of multi-modal AI technologies to build and scale generative AI applications Paper presented at 2024 ASEE PSW Conference, Las Vegas, Nevada. 10.18260/1-2--46051

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