Epsilon Theory is Dr. Ben Hunt’s ongoing examination of the narrative machine driving human behavior, political policy and, ultimately, capital markets—an unconventional worldview best understood through the lenses of history, game theory and philosophy.
Dr. Ben Hunt hosts the Epsilon Theory podcast with co-hosts and special guests from financial services, the financial media *gasp* and beyond. The Epsilon Theory podcast is the quickest way to get all of the unconventional perspective, historical context and narrative analysis you’ve come to expect from Epsilon Theory pumped directly into your head.
To understand the impact of catalytic narrative forces, we have to monitor the vital signs of the capital markets they affect. To analyze the big picture through the lenses of game theory and history, we must also examine the details through lenses like volatility, momentum, income, correlation and inflation. These are the indicators of systemic vitality and stress—the fine details we use to fine-tune our worldview. We hope they help you sharpen your understanding of the investable universe.
We’re growing our family of Epsilon Theory contributors to include a broad range of voices on an evolving range of subject matter. If you listen to the podcast, you’ll recognize some of the names as colleagues, partners and friends of Ben from Salient, any number of past lives, and the growing circle of outspoken truth-seekers in financial services and beyond.
Epsilon Theory author Dr. Ben Hunt is frequently quoted in print, radio and TV appearances.
Salient Partners is the proud parent company of Epsilon Theory. Salient is a diversified asset management firm and leading provider of real asset and alternative investment strategies for institutional investors and investment advisors.
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Vicarious (a buzzy Silicon Valley company developing AI for robots) say they have a new and crazy-good AI technique called Schema Networks. The Allen Institute for Artificial Intelligence and others seem pretty skeptical and demand a throw-down challenge with AlphaGo (or, failing that, some peer-reviewed papers with commonly used terms and a broader set of tests).
In other AI video game news, Microsoft released a video of their AI winning at Ms. Pacman, with an instructive voiceover of how the system works.
I recently stumbled upon Carl Icahn’s Twitter feed which has the tag line: “Some people get rich studying artificial intelligence. Me, I make money studying natural stupidity.” Me, I think in 2017 this dichotomy is starting to sound pretty quaint. See: Overview of recent FAIR (Facebook Artificial Intelligence Research division) study teaching chatbots how to negotiate, including the bots self-discovery of the strategy of pretending to care about an item to which they actually give little or no value, just so they can later give up that item to seem to have made a compromise. Apparently, while they were at it, the Facebook bots also unexpectedly created their own language.
The quantum age has officially arrived
I’ve been jabbering on and pointing to links about quantum computing and the types of intractable problems it can solve for some time here, here and here, but now Bloomberg has written a long piece on quantum we can officially declare “The quantum age has officially arrived, hurrah!”. Very good overview piece on quantum computing from Bloomberg Markets here.
Your high dimensional brain
We tend to view ourselves (our ‘selfs’) through the lens of the technology of the day: in the Victorian ‘Mechanical age’ we were (and partly are) bellows and pumps, and now we are, by mass imagination, a collection of algorithms and processors, and possibly living in a VR simulation. While this ‘Silicon Age’ view is probably not entirely inaccurate it is also, probably, in the grand scheme of things, nearly as naive and incomplete as the Victorian view was. Blowing up some of the reductions of current models, this new (very interesting, pretty dense, somewhat contested) paper points towards brain structure in 11 dimensions. Shorter and easier explainer here by Wired or even more concisely by the NY Post: “If the brain is actually working in 11 dimensions, looking at a 3D functional MRI and saying that it explains brain activity would be like looking at the shadow of a head of a pin and saying that it explains the entire universe, plus a multitude of other dimensions.”
And finally, three different but complimentary technology-enabled approaches to diagnosing and fighting depression:
A basic algorithm with limited data has shown to be 80-90 percent accurate when predicting whether someone will attempt suicide within the next two years, and 92 percent accurate in predicting whether someone will attempt suicide within the next week.
In a different predictive approach, researchers fed facial images of three groups of people (those with suicidal ideation, depressed patients, and a medical control group) into a machine-learning algorithm that looked for correlations between different gestures. The results: individuals displaying a non-Duchenne smile (which doesn’t involve the eyes in the smile) were far more likely to possess suicidal ideation.
On the treatment-side, researchers have developed a potentially revolutionary treatment that pulses magnetic waves into the brain, treating depression by changing neurological structures, not its chemical balance.