Robotics enables physical hyperdeflation. Labor becomes just electricity & code. Real prices for everything should fall, including cost of living, if fiat also recedes.
As a goal, if your annual crypto dividends can pay for the electricity, you should be able to live off robots.
One way to think about the world is a tug of war between (a) the inflation created by the US federal government, where printed funds prop up politically favored sectors, and (b) the global forces of technological hyperdeflation.
We see this directly with housing. Your rent is high because the Fed diluted you down to bail out banks & prop up mortgage-backed securities. And because the government limits construction via picayune regulations.
Inflation, regulation, subsidy — all to prop up the past.
The transition from an environment where the state steals all the money to pay their cronies and inflate your prices to one of technological plenty will be disruptive, but we have a vision of what’s on the other side: fully automated luxury cryptocapitalism.
China doesn’t make any bones about it. All must hail the ruling party.
“Chinese theaters were directed to air at least two propaganda films per week to celebrate the 100th anniversary of the Chinese Communist Party.” cbr.com/chinese-theate…
In seriousness this is an excellent q that would benefit from mapping to historical events.
The canonical example is the fall of the Western Roman Empire to Odoacer and the barbarians.
A contemporary one *might* be Gorbachev’s capitulation followed by Russia in the 90s.
But that last example is interesting because the capitulation of that weak man (Gorbachev) led to *good* times for much of the former Warsaw Pact, though arguably not Russia itself till its recovery under Putin.
The book is worth reading. It’s interesting because it has the ring of truth on many issues.
For example, the construction of markets is itself not entirely a free market phenomenon. Force is often involved. There is a “beyond good and evil” aspect to it. bitcoinmagazine.com/culture/bitcoi…
Btw, here we are defining “bipartisan” as pro-communist and anti-communist, with Sulzberger’s inheritance very much on the pro-communist side of the aisle.
There are dozens of graphs like this which just aren’t part of people’s mental models.
How do you use machine learning to control a drone without worrying it’ll crash or do something weird?
This group says that by separating out the deterministic behavior and using ML only on the stochastic component, they can give formal guarantees for safety and robustness.
They fuse learning and control theory to derive error bounds on their (learned) controllers, ensuring the drone’s trajectory remains within a specified set.
And they show a demo that the math works via a drone that skims the ground.
In addition to this continuous correction (keeping errors within a known ball in trajectory space) they do a discrete correction that forces learning to only occur subject to specific cleverly chosen invariants.
I love this kind of paper b/c the experiments show the math works.
- logical argument (list premises, derive lemmas, show graphs, drive to conclusion)
- listicle (thematically related bullets in any order)
- story (characters, plot, conflict, novelistic suspense)
What other structures do you find helpful?
The style of a piece is often implicit. It’s the kind of thing GPT-3 infers automatically.
But it can be useful to state explicitly. For example, you don’t want to write a research paper like a mystery novel. Put the conclusion in the headline, not after 200 pages of suspense.
Here’s another one that’s useful for academic talks:
- tell them what you are going to tell them
- tell them
- then tell them what you told them
Also, put the basic material up front so everyone gets something out of it, and the advanced material towards the end.