The Securities and Exchange Comission punted again on allowing a passive Bitcoin ETF to enter the market. It failed to approve the VanEck SolidX Bitcoin Trust, instead opting to open a commentary period to address several questions around Bitcoin price formation and the health of the exchanges. A similar outcome faces the Bitwise Bitcoin ETF. You can tell I am not a fan of this waffling, and there are two core reasons: (1) the years-long delay and uncertainty is responsible for financial damage to both traditional and crypto investors, and (2) the premise of the objections misunderstand the environment of the Internet and the way our world is shaping up in the 21st century.
Today's corporations and governments are in the business of defining the balance of these aspects of our participation in society and the economy. Beliefs about the immutability of different attributes about what makes a person (or an employee) and how economies are built (cutting the pie, vs. growing the pie) determine the policy decisions you make, top down. As the core example this week, let's take Deutsche Bank. Facing pricing pressure and headwinds in several of its businesses, Deutsche is responding with a plan to fire 18,000 employees by 2022 and an announced investment of €13 Billion in technology and innovation by 2022. They even spun up a hipster-colored neobank as a proof point. Wall Street ain't buying it.
However, mastery is not immune to automation. As a profession, portraiture melted away with the invention of the Camera, which in turn became commoditized and eventually digitized. The value-add from painting had to shift to things the camera did *not* do. As a result, many artists shifted from chasing realism to capturing emotion (e.g., Impressionism), or to the fantastical (e.g., Surrealism), or to non-representative abstraction (e.g., Expressionism) of the 20th century. The use of the replacement technology, the camera, also became artistic -- take for example the emotional range of Fashion or Celebrity photography (e.g., Madonna as the Mona Lisa). The skill of manipulating the camera into making art, rather than mere illustration, became a rare craft as well -- see the great work of Annie Leibovitz.
How do the Americans and the Chinese have such different ethical takes on privacy, self-sovereignty, media, and the role of government? We can trace the root cause to the DNA of the macro-organism in which individuals reside, itself built over centuries and millenia from the collective scar tissue of local human experience. But there is more to observe. The technology now being deployed in each jurisdiction -- like social credit, surveillance artificial intelligence, monitored payment rails, and central bank cryptocurrency -- will drive a software architecture into the core of our societies that reflects the current moment. And it will be nearly impossible to change! This is why *how* we democratize access to financial services matters. We must be careful about the form, because we will be stuck with it like Americans are stuck with the core banking systems from the 1970s. But the worry is not inefficiency, it is programmed social strata.
In the long take this week, I try out a contrarian point of view on personal finance chatbots. Trim, a savings chatbot, just withdrew support from Facebook Messenger. While lots of other chatbots are still invested in conversational banking, what could we take away from the counterfactual of chatbots failing to get B2C traction? What is the impact on the rest of the platform wars waged by Amazon, Google, and Tesla for connected homes, cars, and the Internet of Things?
I came upon this announcement by Stephen Wolfram recently: Finally We May Have a Path to the Fundamental Theory of Physics… and It’s Beautiful. Wolfram is a theoretical physicist turned mathematician, computer scientist, and entrepreneur responsible for the rigorous Mathematica software. After a career of building one of the most advanced computational packages ever created, he is returning to the question that endlessly captivates geniuses — what is the equation at the heart of our universe?
Is there one unifying stroke of the pen that can connect conventional physics, general relativity, and quantum mechanics into a single whole? Wolfram is not conventional, and I cannot do justice to his thinking both given its complexity and rigor. He claims to have found one such answer, which I will try to sketch. But what drew my atten
The image is taken from an AI paper which explains how to use generative adversarial networks (i.e., GANs) to hallucinate hyper realistic-imagery. By training on hundreds of thousands of samples, the model is able to create candidates representing things like “just a normal dude holding a normal fish nothing to see here”, and then edit out the ones that are too egregious.
The reason the stuff above is so scary is actually that you can mathematically transition in the space between images. So for example, you could move between “a normal dude” and “just a normal fish” and have nightmare fish people. Or you could create a DNA root for an image which is part dog, part car, and part jellyfish. Check out the video below and the very accessible https://www.artbreeder.com/ website to see what I mean.
In this episode, we connect with serial founder Ohad Samet, CEO of TrueAccord. Ohad has been working in fintech machine learning for a decade and a half, applying multi-dimensional mathematics to consumer finance. The result? A more empathetic approach to the traditionally gnarly problem of debt collection.
What we know intuitively, and what the software shows, is that the pixelated image can be expanded into a cone of multiple probable outcomes. The same pixelated face can yield millions of various, uncanny permutations. These mathematical permutations of our human flesh exit in an area which is called “latent space”. The way to pick one out of the many is called “gradient descent”.
Imagine you are standing in an open field, and see many beautiful hills nearby. Or alternately, imagine you are standing on a hill, looking across the rolling valleys. You decide to pick one of these valleys, based on how popular or how close it is. This is gradient descent, and the valley is the generated face. Which way would you go?
This week, we look at a breakthrough artificial intelligence release from OpenAI, called GPT-3. It is powered by a machine learning algorithm called a Transformer Model, and has been trained on 8 years of web-crawled text data across 175 billion parameters. GPT-3 likes to do arithmetic, solve SAT analogy questions, write Harry Potter fan fiction, and code CSS and SQL queries. We anchor the analysis of these development in the changing $8 trillion landscape of our public companies, and the tech cold war with China.