Programmable Money & Auto Public Offerings

Category: Note, Narrative, Rabbit Hole

Programmable money

I’ve recently — perhaps belatedly — developed an interest in blockchain, and particularly in Ethereum. Not so much in trading crypto-currencies, but more in the realm of the type of ‘Smart Token’ protocols being developed by Bancor. As I start to process the implications of smart contracts I’m convinced that we are currently at Day Zero of a massive disruption. To quote Mike Goldin on one dimension of this disruption: “What blockchains give us, fundamentally, is programmable money. When you can program money, you can program incentives. When you can program incentives, you can kind of program people’s behavior.”

Another week, another set of ‘human’ skills which algorithms are mastering: Google demonstrates both an algorithm for tastefully selecting landscape photography, which is almost as good as a pro photographer, and, from the DeepMind division, “a new family of approaches for imagination-based planning (and) architectures which provide new ways for agents to learn and construct plans to maximize the efficiency of a task.”

Rough translation: AI which has the rudimentary ability to consider potential consequences of an action (‘imagine’) and plan ahead result in a higher success rate than AIs without this ability.

ImageNet: the data that changed AI research

Long, terrific overview of the history and impact of the ImageNet data set: “One thing ImageNet changed in the field of AI is suddenly people realized the thankless work of making a dataset was at the core of AI research. People really recognize the importance — the dataset is front and center in the research as much as algorithms.”

Auto Public Offering

Generally, ‘automation of white collar work’ is such an obviously disruptive category of AI — and near-term economic earthquake for many industries — that there is not much to say about it. However, this short piece by Bloomberg a few weeks back caught my eye: Apparently Goldman has automated (or at least mapped out how to automate) half the tasks needed to prepare for an IPO, thus replacing the work previously done by associates earning $326,000 a year. As Bill Gates famously said: “Be nice to nerds. Chances are you’ll end up working for one.”

The paradox of historical knowledge

And finally, I shared a pretty hefty quote from “Homo Deus: A Brief History of Tomorrow” by Yuval Noah Harari last week related to algorithms and self. On a completely different topic, the book also contains a fantastic quote on the paradox of historical knowledge: “This is the paradox of historical knowledge: Knowledge that does not change behavior is useless. But knowledge that changes behavior quickly loses its relevance. The more data we have and the better we understand history, the faster history alters its course, and the faster our knowledge becomes outdated.”

epsilon-theory-programmable-money-auto-public-offering-august-1-2017.pdf (421KB)