The Deep Learning Artificial Intelligence Playbook by Carlos E. Perez involves the interplay of Computer Science, Physics, Biology, Linguistics and Psychology. In addition to that, it is technology that can be extremely disruptive. The ramifications to society and even our own humanity will be profound.


Extremely disruptive

In addition to that, it is technology that can be extremely disruptive.The ramifications to society and even our own humanity will be profound. There are few subjects that are as captivating and as consequential as this. Surprisingly, there is very little that is written about this new technology in a more comprehensive and cohesive way. This book is an opinionated take on the developments of Deep Learning AI.

Business Context

One question many have will be "how to apply Deep Learning AI in a business context?" Technology that is disruptive does not automatically imply that its application to valuable use cases will be apparent

Monetize Deep Learning

For years, many people could not figure out how to monetize the World Wide Web. We are in a similar situation with Deep Learning AI. The developments may be mind-boggling but its monetization is far from being obvious. This book presents a framework to address this shortcoming.

Intuition Machines

We’ve come full circle here, where we establish that the new kind of AIs, known as Deep Learning, is intrinsically intuition machines. That this understanding can help us better leverage this new technology. Finally, that the existential threat of a super-intelligence may perhaps be in the development of altruistic automation.


A book that's worth much more than its price!

“ People ask me for recommendations on how to get a big picture of AI. Carlos' book is the answer. Very well-written, insightful and comprehensive. The book starts with an introduction to the entire AI landscape, going beyond deep learning. Then it continues to the principles and best practices, followed by cutting-edge research. Many of the ideas actually lead towards what we call AGI (general AI) The book takes a deep dive into "meta learning (learning to learn)", which I believe is the most efficient way to automate engineering of a thinking machine: bootstrapping itself and recursively self-improving its adaptability.”

- Marek Rosa

A Helpful Reference and Strategy Guide

“Carlos has done a terrific job examining the intuition underlying deep learning and explored how such technology can be strategically valuable in many domains. His playbook has given me great inspiration on the latest topics and viewpoints for my deep learning lectures. Our students and alumni consider this a helpful reference and strategy guide as they find new uses for deep learning and AI in industry.”

- Ellick Chan, PhD, MBA
Adjunct Lecturer MSiA 432: Deep Learning
Northwestern University

Second to None

“Carlos is second to none is his ability to synthesize all the fast-moving deep learning developments. In his book, he gives a compelling overview on the state of deep learning and gets to the heart of the issue on how enterprises ought to structure their thinking. Enterprises will be increasingly pressured to weave machine intelligence into their businesses to gain or maintain their edge. This book gives them a fast, digestible way to start thinking about it" ”

- Waikit Lau
Serial Machine Learning Entrepreneur

A Refreshingly Unique Approach

“I got this book in early draft edition and only now have a had a chance to read it. This is a refreshingly different approach to AI It is easy to read and at the same time covers a lot of complexity and detail. ”

- Ajit Jaokar
Director of AI / Deep Learning Lab for Future Cities
University of Madrid

I Love It

“Chapters 3, 4, 8 and 9. and your approach thru the lens of intuition!”

- John Seely Brown
Author and cofounder of the Institute for Research on Learning

Recent Articles

Why AlphaGo Zero is a Quantum Leap Forward in Deep Learning

The 1983 movie “War Games” has a memorable climax where the supercomputer known as WOPR (War Operation Plan Response) is asked to train on itself to discover the concept of an un-winnable game. The character played by Mathew Broderick asks “Is there any way that it can play itself?”34 years later, DeepMind has shown how this is exactly done in real life! The solution is the same, set the number of players to zero (i.e. zero humans).

Why Probability Theory Should be Thrown Under the Bus

So, what’s Yann LeCun talking about when he says “he’s ready to throw Probability Theory under the bus”? This article attempts to explore this sentiment.

Natural Stupidity is more Dangerous than Artificial Intelligence

Do you know what’s more dangerous than artificial intelligence? Natural stupidity. In this article, I will explore natural stupidity in more detail.

Taxonomy of Methods for Deep Meta Learning

Let’s talk about Meta-Learning because this is one confusing topic. I wrote a previous post about Deconstructing Meta-Learning which explored “Learning to Learn”.

The Author
Mr. Perez has been a professional software architect and developer focused on developing software systems from concept to production, since 1993. Mr. Perez has 20 years experience developing software. Since 2000, he has primarily held technical architect roles in software development. He was the head architect in a venture capital funded start-up company developing optimization solutions for B2B exchanges. Mr. Perez has worked for IBM Corporation's Internet Division and T.J. Watson Research. He has a diverse experience working in several industries and US federal agencies.