Artificial Intelligence Business: How you can profit from AI

Przemek Chojecki

• Publisher: Packt Publishing
• Year: 2020
• ISBN:
  9781800563469
• Edition: 1
• Topic: Computer Science
• Subtopic: Artificial Intelligence (AI) & Semantics
• Index: Computer Science

The concise guide to artificial intelligence for business people and commercially oriented data scientistsKey Features• Find out how artificial intelligence is shaping the future of businesses• Discover how AI influences the society and its politics and economy• Explore the future of AI and its applicationsBook DescriptionWe'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.What you will learn• Find out how AI helps in building innovative cultures in enterprises• Understand how AI boosts start-ups• Discover modern AI trends in the field of manufacturing and logistics• Explore the benefits of text and image generation applications• Study popular machine learning trends and their usage• Uncover the uses of AI in politics and societyWho this book is forThis book is for artificial intelligence enthusiasts or anyone with a business background who wants to learn how AI can scale up businesses.

Trends in Artificial Intelligence

From a business perspective, what counts is how Artificial Intelligence can make you money. At this point in a book, I hope I’ve conveyed the general framework that AI is here to help you automate and optimize business processes with which you deal daily. It’s supposed to make you faster, more creative, and more efficient in what you do, and by that, give you some time and money back.

In this chapter, I will look at various business domains and go through how AI is already used in practice. From the most striking applications in retail to healthcare and video games, we’ll go over use cases that made headlines in recent years. Moreover, I’ll speculate about the general directions of AI applications and how your organisation can benefit from them.

Regardless of your geographical location or your budget, you’ll be able to use AI in your organisation thanks to democratisation trend within the community. Open-source code available on Github allows you to pick recent research, tune it quickly with your data, and start using it to solve your problems. The whole process is fast, especially if you know a bit of Python yourself.

Before diving in more specific domain-trends, I’d like to point you to general meta-trends that appear in applied AI. Those are:

1. Autonomous machines
2. Automated processes
3. Optimized processes with human supervision

Autonomous machines trend is about making real-world robots, vehicles, or otherwise constructed things into independent self-sufficient (to a large extent at least) beings that perform one particular task very well. The simplest example is iRobot Roomba, an autonomous vacuum cleaner, which is already widely used in American households. Or think about self-service checkout. In this category, we will have autonomous cars (e.g. Tesla) or autonomous sorting machines operating in Amazon warehouses.

Automated processes trend is to take repetitive processes and use algorithms to make them fully automatic. The oldest example of this is a calculator, which led to more advanced computing machines, and the automation of computations. More advanced uses are, for example, macros in spreadsheets or connecting various applications thanks to Zapier or similar solutions. The current work done in this space often goes under the name Robotic Process Automation, and some notable players are Automation Anywhere, UIPath, and Blue Prism. On the other hand, automated processes also encompass healthcare problems: from diagnostics to drug design.

Optimized processes is a category where machines are supervised by humans, and eventually, it is up to a supervisor to choose the optimal answer from insights provided. Great examples can be found in marketing when one wants to optimize ad spend and effectiveness, by automatic A/B testing, looking for patterns and insights in marketing data. Nevertheless, optimization occurs everywhere, from marketing to real estate, from retail to manufacturing, as we will see in this section. Optimization is the most common reason why AI is employed at all. Machine learning builds upon statistics using most cutting edge hardware to deliver outstanding optimization performance across a variety of fields.

All in all machine learning is driving changes at three levels:

• tasks and occupations, for example, using computer vision to free up radiologists’ time in detecting potential cancer cells.
• business processes, for example, Amazon warehouses introducing robots and optimization algorithms to their workflow.
• business models, for instance, going from pricing for an individual product (song, movie) to a subscription model based on personalised recommendations a’la Netflix or Spotify.

We’re still early in the process, and hence machine learning systems do not replace entire jobs or processes but rather boost and complement human workers. AI is applied whenever a task is tedious and repetitive and can be automated, hence freeing up human time. For example, chatbots used commercially in customer service are not meant to replace employees entirely but make them focus only on the most unusual cases where a personal touch is necessary.

This approach at the current stage of research is also the only one feasible in production, as building a technology that would commit no error is either too hard or too costly right now. Nevertheless, you...