Book Image

Artificial Intelligence Business: How you can profit from AI

By : Przemek Chojecki
Book Image

Artificial Intelligence Business: How you can profit from AI

By: Przemek Chojecki

Overview of this book

We’re living in revolutionary times. Artificial intelligence is changing how the world operates and it determines how smooth certain processes are. For instance, when you go on a holiday, multiple services allow you to find the most convenient flights and the best hotels, you get personalized suggestions on what you might want to see, and you go to the airport via one of the ride-sharing apps. At each of these steps, AI algorithms are at work for your convenience. This book will guide you through everything, from what AI is to how it influences our economy and society. The book starts with an introduction to artificial intelligence and machine learning, and explains the importance of AI in the modern world. You’ll explore how start-ups make key decisions with AI and how AI plays a major role in boosting businesses. Next, you’ll find out how media companies use image generation techniques to create engaging content. As you progress, you’ll explore how text generation and AI chatbot models simplify our daily lives. Toward the end, you’ll understand the importance of AI in the education and healthcare sectors, and realize the risks associated with AI and how we can leverage AI effectively to help us in the future. By the end of this book, you’ll have learned how machine learning works and have a solid understanding of the recent business applications of AI.
Table of Contents (10 chapters)

Fundamental concepts

Machine learning from a theoretical standpoint is still a relatively new domain, and theres a lot of theory missing, which would explain why certain fundamental concepts work in some cases and not in others. As of now, machine learning and data science are more practical and experimental sciences, similar to experimental physics, rather than state-and-prove pure mathematics.

Nevertheless, I firmly believe that were going to see a more mathematical approach to neural networks, which would help clarify fundamental concepts. Such a theory would likely be within probability theory with elements of dynamical systems (training dynamics), representation theory (feature engineering, representation characteristics), and probably much more. As such, it would find a considerable appeal among mathematicians and theoretical computer scientists.

Currently, we dont even know how to answer the basic questions, like:

  • how to select models...