Название: The Secrets of AI: a Math-Free Guide to Thinking Machines
Автор: Mukesh Borar
Издательство: Independently published
Год: 2023
Страниц: 117
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.19 MB

AI is undoubtedly the most critical technology that we must understand today. It is affecting everyone’s career, business and profession. However, AI is a complex and mysterious technology. To understand it, we have to climb a mountain of cryptic mathematical concepts and formulas, and success may still be elusive.

‘The Secrets of AI’ addresses this and explains AI in a simple, math-free language. This book sidesteps arcane algorithmic details and presents AI from the important perspectives of – intelligence, engineering, design, learnability, trust and business. It provides deep insights into the symbiotic relationships between data, learning and intelligence.

The book has a strong focus on AI engineering. The AI development lifecycle is illustrated with an exhaustive case study on AI-driven live coverage of sports. It includes domain study, model architecture, feature engineering, model training, deployment and feedback learning. The book describes several design patterns and heuristics that are useful for building successful AI-powered systems.

Math and magic are two words that can easily be associated with AI. How machines talk, listen, read, compose, observe, and act is nothing short of magic. For many tasks, machines already perform better than the experts in the field. A lot of this is happening because machines can learn, and they are getting better at it with each passing day. Machines learn simply by observing massive amount of data. At times, this appears magical even to those who are from the AI fraternity.

Often the magic stems from the sophisticated mathematics that powers the Machine Learning algorithms. The math involved can range from basic arithmetic to advanced concepts like calculus. It includes advanced techniques from the disciplines of statistics and probability. The mystery of AI deepens with the usage of inscrutable neural networks, which are learned through complex mathematical operations.

However, we cannot just live in awe of AI; we must understand it. AI is mastering more and more human activities. It is dramatically expanding the role of computers in our lives. Decisions made by the thinking machines already touch millions in their daily lives. Today, it is a must to have a good appreciation of what goes on behind the scenes. AI knowledge is critical, not just for software professionals but also for those who approve it, invest in it, and use it.

It is here that math can become a hindrance. Acquiring deep knowledge of mathematics is not everyone’s cup of tea. This, at times, is true even for software professionals. Math can surely come in the way of developing a good understanding of AI. It can inhibit us from having an informed opinion on AI. That’s not how it should be. Math need not be a pre-requisite to know more about AI. AI is too important a technology to not learn about for want of mathematical prowess.

This book reveals invaluable AI success secrets to the founders, architects, engineers, analysts, and program managers.