The End of Code: A Revolution in Computer Science, Part I

I'm Jeff Payne and I work as the Chief Operating Officer at Greyfeather Capital.  One of my struggles in this role has been finding the right words to convey the unique and revolutionary nature of the technology that powers Greyfeather’s strategy. 

That being the case, you can imagine my excitement when I found Wired Magazine’s article “The End of Code” written by Jason Tanz of the June 2016 issue. This article explains, in layman’s terms, the type of artificial intelligence that Greyfeather is using and how it is a radical departure from the computer code used by many of today's quantitative hedge funds. Over the course of three posts, I will highlight some key points from that article that provide context to the manner in which Greyfeather will disrupt the field of investment management. 

For decades, computer science has been ruled by the programmers.  Those who write the best code reign supreme.  The process is simple to articulate, but takes extreme talent to execute – the coder writes rules in a computer programming language and the composite logic derived from those rules dictates outcomes.  The collection of these rules is often called a “black box” from which outputs seem to magically appear.  Furthermore, it was long assumed that the more elegantly written code you write, the more exactly you could approximate the functionality of the human brain.

However, recent developments in the understanding of the human brain, have caused computer scientists to rethink that presumption.

Wired Magazine’s Jason Tanz notes that “the brain [isn’t] a black box at all.”  It turns out, in the mid-1950’s, psychologists began to argue that, “people… were not just collections of conditioned responses.  They absorbed information, processed it, and then acted upon it.  They had systems for writing, storing, and recalling memories.”

It is this revelation that has allowed scientists to create the modern field of artificial intelligence (AI), bring the discipline of machine-learning to its forefront, and make deep learning neural networks its most potent weapon.

The contrast in this computer science paradigm shift cannot be understated.  As Tanz notes, “If in the old view programmers were like gods, authorizing the laws that govern computer systems - now they’re like parents or dog trainers.”

“If you want to teach a neural network to recognize a cat… you don’t tell it to look for whiskers, ears, fur, and eyes.  You simply show it thousands and thousands of photos of cats, and eventually it works things out.”

This is Greyfeather’s approach.  If you want to teach a neural network to recognize a stock likely to outperform the upcoming month’s median return, you don’t tell it to look for momentum characteristics, attractive valuations, etc.  You simply show it copious market and fundamental data and the neural network learns to make predictions that no team of stock analysts can match.

The application of this revolutionary technology is why Greyfeather Capital is not just another quant hedge fund.  Rather we are a pioneer of artificial intelligence in the field of investment management.