Background, Transition, and the Future of Computing

Welcome to the world of Cognitive Computing with IBM Watson. We'll be starting the book by learning the answers to the following questions:

• What is AI and why do we need AI? Why can't we just use regular, traditional technologies?
• What are some examples of transitioning from regular technology to new, AI-based technology?
• Are there some disadvantages to AI technology, and can it be used in a negative fashion?
• How can I get started developing with IBM Cloud?
• What do I need in terms of hardware and software to learn through this book?

This book will also take us through some of the ways that the machine learning technology itself can be implemented for similar use cases. This book assumes you're already somewhat tech-savvy and familiar with application development and programming. We'll be going through implementations in Python, because the Watson Developer Cloud provides language-specific SDKs to access the Watson REST APIs and you mostly have a congruent coding experience, even across languages.

In this chapter, we will discuss the following topics:

• Transitioning from conventional to cognitive computing
• Limitations of conventional computing
• Solving conventional computing problems
• Workings of machine learning
• Cons of machine learning
• Introduction to IBM Watson
• Hardware and software requirements