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

MySQL

MySQL is an open source relational database system that's used by websites such as Facebook, Flickr, Twitter, and YouTube because it supports stored procedures, cursors, triggers, and all the SQL database features.

Advantages of MySQL

  • Simple and easy to use
  • Open-source
  • Good performance with a wide range of queries and primary keys
  • Effectively processes data that's GBs to a few TBs in size, with a limited level schema complexity
  • Follows the ACID methodology accurately
  • Follows the schema-on-write methodology where it pre-validates the records during insertion

Disadvantages of MySQL

  • Difficult to scale MySQL after a certain level.
  • Designed to run on a single machine, which means a single point of failure and lesser availability.
  • Being a part of the relational database system focuses on normalization and data duplication, which results in multiple joins. After a while, when data grows exponentially, this leads to a massive...