Source: Deep Learning on Medium
A New Book on the Emergence of Empathy and Therefore General Intelligence
It is early 2020 and the world is on a trajectory towards a global pandemic across covering 5 continents. Despite humanity’s incredible advances in the last millennium, we have yet to conquer or even fully understand the working of microbes. I am reminded of the Orson Well’s War of the Worlds. It wasn’t us (humans) who defeated the conquering aliens, but rather the ‘lowly’ microbes that won the war on our behalf.
COVID-19, as it is named by the World Health Organization (WHO), is a problematic coronavirus that has a tendency to remain in a host without immediate symptoms. It has been reported that it has an incubation period of 14–24 days. This lack of eagerness for the virus to attack is what allows it to spread undetected.
This is my motivation for releasing this book as a work in progress. That is incomplete but under construction. The truth is, I write to learn. I’ve written two books in 2017, The Deep Learning Playbook and Artificial Intuition. Both books center around the narrative that the emerging machine learning algorithm known as Deep Learning is, in fact, humanity’s first discovery of what I called ‘artificial intuition’.
This idea was inspired by Daniel Kahneman’s book ‘Thinking Fast and Slow’ which depicted human cognition as consisting of two modes. A fast kind that he labeled System 1, which in folk psychology would be recognized as intuition. A slow kind that he labeled System 2, which can be recognized as deliberate thought, reasoning or rationality.
It took at least two years before this notion that Deep Learning is intuition began to be accepted. In the recently concluded AAAI2020 conference, the Turing award recipients (Geoffrey Hinton, Yoshua Bengio and Yann LeCun) spoke in a panel with Daniel Kahneman to discuss how the narrative of Deep Learning as System 1 (or intuition) can inspire innovation in artificial intelligence.
Good ideas eventually find their way into broader acceptance and appeal.
In the two years since I wrote my books about intuition, I have explored further on the nature of human cognition and have begun to recognize a path that could lead to what is known as Artificial General Intelligence (AGI). AGI distinguishes itself from Artificial Intelligence (AI) in that it seeks to create synthetic brains that are capable of human-level cognition.
My formal educational background is in computer science and physics. When I first embarked on my study of Deep Learning, I had the hope that ideas physics cross-fertilize the emerging field. I had sought the help of Peter Wittek, a physicist working on quantum-inspired machine learning. Peter, unfortunately, passed away last year while on a mountain climbing expedition in the north of India. He was in his tent when an avalanche occurred, burying him under the snow. His body was never found. In my book Artificial Intuition, I speculated that there might be a connection with the tensor networks found in the Holographic principle in Physics and that of the networks found in Deep Learning. This idea has yet to be fully explored.
When you write about new subjects, you have to acknowledge that you could be wrong about many of your ideas. Erwin Schrödinger’s much acclaimed ‘what is life?’
A writer also has to remain humble enough to know that there is knowledge about what you are writing about that you may never know existed. Charles Babbage never knew about electrical circuits when he built his mechanical computer the Analytic Engine. Civilization would be entirely different if he made the connection and invented the electric computer in the 19th century. We could have had electrical computers over 100 years earlier.
The curious nature about learning almost anything is that the inspiration must be generated from within. It reminds me of the movie Inception where the protagonist Cobb remarks “An idea is like a virus. Resilient. Highly contagious. And even the smallest seed of an idea can grow. It can grow to define or destroy you.” The movie revolves around a scheme to plant an idea into the mind of another person. Cobb says “You need the simplest version of the idea-the one that will grow naturally in the subject’s mind. Subtle art.”
I’ve been able to grasp the complex ideas about human cognition because I wrote about it. Writing is a generative process. Surprisingly, generative processes are how you learn. In my journey, I have been influenced by several books that I highly recommend. Here’s my recommended order for reading them:
The Emergence of Everything by Harold Morowitz
World Beyond Physics: The Emergence and Evolution of Life by Stuart A. Kauffman
The Nature of Technology: What It Is and How It Evolves by W. Brian Arthur
The Tangled Tree: A Radical New History of Life by David Quammen
Principles of Biological Autonomy by Francisco Varela
The Strange Order of Things: Life, Feeling, and the Making of Cultures by Antonio Damasio
Intuition Pumps and Other Tools for Thinking by Daniel C. Dennett
The Beginning of Infinity: Explanations That Transform the World by David Deutsch
Surfaces and Essences: Analogy as the Fuel and Fire of Thinking by Douglas Hofstadter and Emmanuel Sander
Mind in Motion: How Action Shapes Thought by Barbara Tversky
Wayfinding: The Science and Mystery of How Humans Navigate the World by M. R. O’Connor
Why Greatness Cannot Be Planned: The Myth of the Objective by Kenneth O. O. Stanley
Strange Tools: Art and Human Nature by Alva Noë
The Enigma of Reason by Hugo Mercier and Dan Sperber
The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future by Kevin Kelly
Possible Minds: Twenty-Five Ways of Looking at AI by John Brockman — editor
One could imagine that all these great books could be combined into a consistent whole. That is, of course, is not this book, but I hope you will find that many of the organizational thought patterns found in there will also be found while you read my book.
You can get the pre-released version of the book at Gumroad: https://gumroad.com/l/rDqnm