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Coding with ChatGPT and Other LLMs

Coding with ChatGPT and Other LLMs

By : Dr. Vincent Austin Hall, Dr. Vincent Austin Hall, Chigbo Uzokwelu
4 (4)
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Coding with ChatGPT and Other LLMs

Coding with ChatGPT and Other LLMs

4 (4)
By: Dr. Vincent Austin Hall, Dr. Vincent Austin Hall, Chigbo Uzokwelu

Overview of this book

Keeping up with the AI revolution and its application in coding can be challenging, but with guidance from AI and ML expert Dr. Vincent Hall—who holds a PhD in machine learning and has extensive experience in licensed software development—this book helps both new and experienced coders to quickly adopt best practices and stay relevant in the field. You’ll learn how to use LLMs such as ChatGPT and Bard to produce efficient, explainable, and shareable code and discover techniques to maximize the potential of LLMs. The book focuses on integrated development environments (IDEs) and provides tips to avoid pitfalls, such as bias and unexplainable code, to accelerate your coding speed. You’ll master advanced coding applications with LLMs, including refactoring, debugging, and optimization, while examining ethical considerations, biases, and legal implications. You’ll also use cutting-edge tools for code generation, architecting, description, and testing to avoid legal hassles while advancing your career. By the end of this book, you’ll be well-prepared for future innovations in AI-driven software development, with the ability to anticipate emerging LLM technologies and generate ideas that shape the future of development.
Table of Contents (19 chapters)
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Part 1: Introduction to LLMs and Their Applications
5
Part 2: Be Wary of the Dark Side of LLM-Powered Coding
10
Part 3: Explainability, Shareability, and the Future of LLM-Powered Coding
14
Part 4: Maximizing Your Potential with LLMs: Beyond the Basics

Summary

Looking ahead, the future of LLMs in software development is one filled with potential, both in terms of technical advancements and the societal changes that will accompany them. Emerging trends such as domain-specific and multimodal LLMs, along with real-time collaboration, will expand the horizons of what developers can achieve. At the same time, the impact of these technologies will democratize coding and streamline development processes.

However, challenges around ethics, bias, and code quality remain significant, and addressing these issues will be critical as LLMs continue to evolve. Despite these challenges, the opportunities offered by LLMs—including scalable development and enhanced productivity—are immense. The key for developers will be to adapt, innovate, and take full advantage of these transformative tools.

Ultimately, while we can’t get code from the future, we can shape it by embracing these new technologies and imagining what we&...

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