Precision weapons are shifting the center of gravity from firepower to logistics. Industrial capacity, redundancy, and resilience may matter more than having the most advanced platforms.
It's amazing how consistently thr lower memory cost have expanded the set of economic viable applications : cheaper hardware doesn't just improve existing software it also enables software that was not possible before
Zero interest rates kept many weak companies alive but they also have give great companies time to find product market fit, and the hard part is to separate the two in hind sight
People often compare this to the dot-com bubble but today's leaders are generating very big cash flows => a valuation reset and a business collapse are two very different things
Since it's the obvious objection : the inversion to recession relationship is an observed regularity and not a mechanism.
The lead times have varied a lot : the 2006 inversion preceeded the Great Recession by about 17 months while the 2019 inversion was followed much quickly by a recession. Recession was ultimately triggered by the pandemic more than by the curve.
The choice of the spread is important too. In 2019 the 10y–3m inverted clearly while the 10y–2y stayed only smally negative for a short period.
This animation simply lets watch the full Treasury curve evolution month by month and see how inversions appeared before modern US recessions.
Data : monthly Treasury yields from 3m to 30y (Fed H15 via FRED) with NBER recession dates with CSV download included.
Everything is hand rolled SVG and vanilla JavaScript with no charting libraries.
This is the good example of positive externalities => some of the most valuable things in society like the friendships, communities or informal support networks create realbenefits that are important but hard to monetize
One of the most interesting thing about commodity bottlenecks is that they often accelerate substitution ; scarcity can end up by making a material being less important
An interesting part here is probably manufacturing and not the motor itself : going from a prototype to something you can mass produce reliably is often the hard part
All important technologic revolution can turn into an infrastructure revolution => the railroads, electricity etc … so the technology can be a transformation while the capital cycle becomes in excess
The most worrying part isn't the cheating it's that students seem to be skipping the struggle that learning requires, as one professor put it "Confusion is the sweat of learning"
What to notice is that this wasn't really a startup idea at first but it was someone noticing that commercial wireless keyboards had solved a problem that the DIY ecosystem had not; a number of successful products seem to be from bringing an existing capability into a community that need it.
AI infras is starting to run into the same land using and energy also as heavy industries : when the datacenters compete for grid capacity water and industrial land at scale the local governments just stop treating them like just advanced softwares
tokenmaxxing is becoming harder to justify could be a change in the labor market => when capital was free the companies optimized aggressively around retention and internal status spending but high rates + slow growth oblige firms to back toward productivity and operating leverage.