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

SQL Databases

These are the row-oriented type of databases. Here, each row of the database is a record. A collection of columns forms a record and is stored in a structure called a table. These collections of tables form the database.

These databases are accessed using SQL. It was developed by two IBM software researchers in the 1970s and it became more and more dominant in the field after that due to its straightforward, understandable syntax, ease of learning, and fewer lines of code being required to use complex functionalities:

Figure 5.2: User database interaction through SQL

In the preceding diagram, user database interaction through SQL is demonstrated, where the efficacy of the SQL architecture to deal with "structured data" is quite visible.

SQL databases work on Atomicity, Consistency, Isolation, and Durability (ACID) properties, which guarantees strong consistencies and isolated transaction behavior. These are crucial while designing...