Generative AI in your office work. How to enhance your daily office workflow with new AI tools.

Welcome to “Generative AI in your office work. How to enhance your daily office workflow with new AI tools”, a comprehensive guide designed to help you master the art of prompting various Language Learning Models (LLMs). This book is structured to take you through the basics of prompting, explore interactions with different LLMs, and demonstrate practical use cases.

About the Author

Bartosz Naskręcki is an adjunct professor, with a background in number theory, algebraic geometry and computational mathematics with recent emphasize on AI enhanced education.

Background

• Education: Bartosz Naskręcki completed his M.Sc. in Mathematics at Adam Mickiewicz University (AMU) in 2010. He then pursued a Ph.D. at the same institution, graduating in 2014, with his studies funded by an EU scholarship. He attended VIII Secondary School in Poznań with a focus on mathematics and computer science.

• Experience: Bartosz Naskręcki has a diverse professional background. Since December 2022, he has been a post-doctoral researcher at the Institute of Mathematics, Polish Academy of Sciences. He has been an assistant professor at Adam Mickiewicz University since October 2014. Additionally, he was a research associate at the University of Bristol (2016-2017) and a postdoctoral research fellow at Universität Bayreuth (2014-2016).

• Contributions: Naskręcki has made significant contributions in the fields of mathematics and crystallography. His research includes the arithmetic aspects of algebraic geometry, with notable work on the generalized Fermat theorem and Zsigmondy bounds for elliptic divisibility sequences. He has published numerous papers in high-impact journals, such as the Journal of Number Theory and Acta Crystallographica. His work has earned him several prestigious awards, including the Diamenty Krystalografii from the Polish Academy of Sciences in 2022 and the STEM Bronze Award for Mathematical Sciences from the UK Parliament in 2017.

Origins of This Work

The idea for this book originated from Bartosz’s experiences and observations in the field of automatic proof generation and recent algorithms like AlphaGeometry. Recognizing the challenges and opportunities associated with prompting LLMs, he embarked on a mission to create a resource that would be both informative and practical for learners and professionals alike.

Motivation

• Identify Gaps: The need to address common challenges and misunderstandings in prompting LLMs.

• Share Knowledge: A desire to share expertise and insights gained from years of hands-on experience.

• Promote Best Practices: Encouraging the adoption of effective techniques and strategies for interacting with LLMs.

Structure of the Book

This book is divided into several sections to provide a structured learning experience:

1. General Introduction: An overview of the book’s objectives and structure.

2. Simple Prompting, Examples, Failed Attempts: Basics of prompting, illustrated with examples and common pitfalls.

3. Interactions with Different LLMs and Platforms: Exploring various LLMs and how to interact with them on different platforms.

4. Use Cases: Demonstrating practical applications of LLMs in various scenarios.

5. Literature and Resources: A compilation of additional reading materials and resources to further your knowledge.

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Thank you for embarking on this learning journey. Let’s dive into the fascinating world of prompting LLMs and unlock their full potential together!

Bartosz Naskręcki