April 3, 2017
Category: Big Data
Scared money can’t win and a worried man can’t love.
― Cormac McCarthy, All the Pretty Horses (1992)
In 1872, noted horseracing aficionado and San Francisco rich guy Leland Stanford (yes, of university fame) commissioned noted photographer and San Francisco smart guy Eadweard Muybridge to apply his path breaking technology of stop-action photography to settle a long-running debate — do all four hooves leave the ground at the same time when horses run? This question had bedeviled the Sport of Kings for ages, and while Stanford favored the “unsupported transit” theory of yes, all four hooves leaving the ground for a split-second in the outstretched position, allowing horses to briefly “fly”, he — as rich guys often do — really, really, really needed to know for sure.
It took Muybridge about 12 years to complete the work, interrupted in part by his murder trial. It seems that Muybridge had taken a young bride (she 21 and he 42 when they married) who preferred the company of a young dandy of a San Francisco drama critic who fashioned himself in faux militaristic fashion as Major Harry Larkyns. After learning that wife Flora’s 7-month old son Florado was perhaps not biologically his, Muybridge tracked Larkyns down and shot him point-blank in the chest with the immortal words, “Good evening, Major, my name is Muybridge and here’s the answer to the letter you sent my wife.” In one of the more prominent early cases of jury nullification (Phillip Glass has an opera, The Photographer, with a libretto based on the court transcripts), Muybridge was found not guilty on the grounds of justifiable homicide despite the judge’s clear instructions to the contrary. Or maybe the jurors were just bought off. Leland Stanford spared no expense in paying for Muybridge’s defense. Gotta get those horse pix.
And eventually he did. Muybridge’s work, The Horse in Motion, settled the question of unsupported transit once and for all.
Yes, all four hooves leave the ground at the same time. But it’s NOT in the outstretched flying position. Instead, it’s in the tucked position, which — because it’s not as romantic a narrative as flying — had never been widely considered as an answer. In fact, for decades after the 1882 publication of The Horse in Motion in book form (a book by Leland Stanford’s fellow rich guy friend, J.D.B. Stillman, who gave ZERO credit to Muybridge for the work … after all, Muybridge was just Stanford’s work-for-hire employee, a member of the gig economy of the 1870s), artists continued to prefer the more narrative-pleasing view of flying horses. Here, for example, is Frederic Remington’s 1889 painting A Dash for the Timber, a work that was largely responsible for catapulting Remington to national prominence, replete with a whole posse of flying horses (h/t to John Batton in Ft. Worth, who knows his Amon Carter Museum collection!).
Okay, Ben, that’s a fun story of technology, art, murder, and rich guy intrigue set in 1870s San Francisco. But what does it have to do with modern markets and investing?
This: Muybridge developed a technology that allowed for a quantum leap forward in how humans perceived the natural world. His findings flew in the face of the popular narrative for how the natural world of biomechanics worked, but they were True nonetheless and led to multiple useful applications over time. Today we are at the dawning of a technology that similarly allows for a quantum leap forward in how humans perceive the world, but with a focus on the social world as opposed to the natural world. Some of these findings will no doubt similarly fly in the face of the popular narrative for how the social world of markets and politics works, but they will similarly lead to useful applications. They already are.
The technology I’m talking about is the biggest revolution in the world today. It’s the ascendancy of non-human intelligences, which I’ve written about in lots of Epsilon Theory notes, from Rise of the Machines to First Known When Lost to Troy Will Burn – the Big Deal about Big Data to The Talented Mr. Ripley to One MILLION Dollars to Two Discoveries. It’s what most of the world calls Artificial Intelligence, which is a term I dislike for its pejorative anthropomorphism. It’s what Neville Crawley calls Big Compute, which is a great phrase, not least for its progression and distinction from the old hat notion of Big Data (h/t to Neville for turning me on to the Muybridge story, too).
The primary impact of Big Compute, or AI or whatever you want to call it, is that it allows for a quantum leap forward in how we humans can perceive the world. Powerful non-human intelligences are the modern day Oracle of Delphi. They can “see” dimensions of the world that human intelligences cannot, and if we can ask the right questions we can share in their vision, as well. The unseen dimensions of the social world that I’m interested in tapping with the help of non-human intelligences are the dimensions of unstructured data, the words and images and communications that comprise the ocean in which the human social animal swims.
This is the goal of the Narrative Machine research project (read about it in The Narrative Machine and American Hustle). That just as Eadweard Muybridge took snapshots of the natural world using his new technology, so do I think it possible to take snapshots of the social world using our new technology. And just as Muybridge’s snapshots gave us novel insights into how the Horse in Motion actually works, as opposed to our romantic vision of how it works, so do I think it likely that these AI snapshots will give us novel insights into how the Market in Motion actually works.
That’s the horse I’m betting on in Epsilon Theory.