Understanding Generative AI Business Applications (PDF)
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The book is organized into three sections: text-based, senses-based, and rationale-based. Each section provides an in-depth exploration of the specific methods and applications of Generative AI. In the text-based section, you will find detailed discussions on designing algorithms to automate and enhance written communication, including insights into the technical aspects of transformer-based Natural Language Processing (NLP) and chatbot architecture, such as GPT-4, Claude 2, Google Bard, and others. The senses-based section offers a glimpse into the algorithms and data structures that underpin visual, auditory, and multisensory experiences, including NeRF, 3D Gaussian Splatting, StableDiffusion, AR and VR technologies, and more. The rationale-based section illuminates the decision-making capabilities of AI, with a focus on machine learning and data analytics techniques that empower applications such as simulation models, agents, and autonomous systems.
In summary, this book serves as a guide for those seeking to navigate the dynamic landscape of Generative AI. Whether you're a seasoned AI professional or a business leader looking to harness the power of creative automation, these pages offer a roadmap to leverage Generative AI for your organization's success.
What You Will Learn
- What are the technical elements that constitute the makeup of Generative AI products?
- What are the practical applications of Generative AI?
- How can algorithms be designed to automate and improve written communication?
- What are the latest Generative AI architectures and algorithms?
Irena has a joint MBA/MA from the University of Southern California and an MS with Distinction in Management and Systems from New York University. She graduated with a BA from the University of Pennsylvania with a major in Economics (summa cum laude).
- Autor: Irena Cronin
- 2024, 1st ed, 248 Seiten, Englisch
- Verlag: APress
- ISBN-10: 8868802821
- ISBN-13: 9798868802829
- Erscheinungsdatum: 21.05.2024
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- Dateiformat: PDF
- Größe: 3.64 MB
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