Book Image

The Artificial Intelligence Infrastructure Workshop

By : Chinmay Arankalle, Gareth Dwyer, Bas Geerdink, Kunal Gera, Kevin Liao, Anand N.S.
Book Image

The Artificial Intelligence Infrastructure Workshop

By: Chinmay Arankalle, Gareth Dwyer, Bas Geerdink, Kunal Gera, Kevin Liao, Anand N.S.

Overview of this book

Social networking sites see an average of 350 million uploads daily - a quantity impossible for humans to scan and analyze. Only AI can do this job at the required speed, and to leverage an AI application at its full potential, you need an efficient and scalable data storage pipeline. The Artificial Intelligence Infrastructure Workshop will teach you how to build and manage one. The Artificial Intelligence Infrastructure Workshop begins taking you through some real-world applications of AI. You’ll explore the layers of a data lake and get to grips with security, scalability, and maintainability. With the help of hands-on exercises, you’ll learn how to define the requirements for AI applications in your organization. This AI book will show you how to select a database for your system and run common queries on databases such as MySQL, MongoDB, and Cassandra. You’ll also design your own AI trading system to get a feel of the pipeline-based architecture. As you learn to implement a deep Q-learning algorithm to play the CartPole game, you’ll gain hands-on experience with PyTorch. Finally, you’ll explore ways to run machine learning models in production as part of an AI application. By the end of the book, you’ll have learned how to build and deploy your own AI software at scale, using various tools, API frameworks, and serialization methods.
Table of Contents (14 chapters)
Preface
4
4. The Ethics of AI Data Storage

4. The Ethics of AI Data Storage

Overview

In this chapter, you will learn about how ethics relate to Artificial Intelligence (AI) by looking at some of the largest industry scandals where AI ran up against morality. We will dive deep into several case studies, examining everything from AI being used to manipulate elections to AI displaying racial and sexist prejudices. We'll implement a simple sentiment classifier to differentiate between positive and negative words and sentences. We'll observe how this works in many cases and display the problematic biases and human stereotypes in the classifier. We'll gain hands-on experience with word embeddings and see how word embeddings can be used to represent how certain words relate to each other.

By the end of this chapter, you'll have learned how to evaluate the ethical aspects of the AI systems you build. You will know how to examine the potential consequences of using AI-based systems, and you'll know...