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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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1
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

Security Considerations and Measures

In this chapter, we shall study the security threats and risks we can open ourselves up to by using AI-generated code, specifically code from Large Language Models (LLMs), as well as how to guard against these and operate in as safe a way as necessary. We need to learn how weaknesses are exploited, even the subtle ones. This can help you to plan, be vigilant, deal with threats, and avoid them. We’ll get into systems for constant monitoring, effective planning, and collaboration with trusted parties.

LLMs are extremely useful for many tasks, including generating code for software; they can debug, document, comment, and test functions, and even architect entire applications. However, they do present a new space for security challenges, one that is shifting all the time.

If a single line of AI-generated code could compromise an entire system or a prompt could accidentally lead to the exposure of sensitive data, then we have to work hard...

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