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

Data in Document Format

For relational databases, data is usually in a tabular form. The file format for tabular data is usually CSV or TSV. However, data in modern web applications is rarely in a tabular form. For example, when we send a tweet on Twitter, we are effectively making a post request to the tweeter's server with the data being a document format. The data in our post request looks as follows:

Figure 10.39: Data in document format

If you are familiar with web programming, you'll notice that this data is in a JSON format. Data in JSON format naturally manifests the structure of the object in object-oriented programming languages such as JavaScript, Python, and Java. Nowadays, the most common data format that web servers are using between their communications is JSON. For web developers, data in JSON format is preferred to work with than data in tabular format, which means NoSQL databases are also preferable over relational databases...