I was having this conversation with several work colleagues. Most companies are still focused on using AI to reduce employment costs, or speed up the same workflows they are running.
Completely adjusting how the business functions to take into account AI is still not on the minds of most businesses. It’s going to require some “creative destruction” (to use the fashionable term) and new companies to really take advantage of this.
MS Word can be a surprisingly good and powerful type setting system if you use its fancier features correctly, like named styles. I used to have a Latex resume and switched to LibreOffice several years ago. It gives me more than enough precise control over layout and styling, with less effort, and it still generates good PDFs.
This completely breaks down under the current reality of AI investment, as players large and small are no longer price-takers. The marginal costs of investment are not constant because we have finite supplies of GPUs, TPUs, memory, hard drives, and power. The Hamiltonian in equations 5 and 6 needs to account for this.
It's not that supply was actually infinite, but you didn't realistically have situations where you said "I want to buy GPUs for a data center" only to be told "there's a 3 year waiting list."
You might have two months after NVidia 3090s came out where they were short, but it is nothing like today.
Citation needed. Industries that faced multi year supply constraints in recent memory include: nuclear power, battery manufacturing, flagship commercial aircraft models, late-stage pharmaceutical safety certification, certain luxury cars, and more.
I did a write-up on the history of the J-curve and some 2026 macro data that supports it for generative AI. The short version: U.S. productivity is climbing again after a decade of stagnation, and the original j curve economist proposes it might be due to AI hitting the upper part of the j-curve.
Q: The J-dip is where capital stock is just about to overtake investment growth, why should it lag the hype trough where presumably value overtakes interest ?
FYI about terminology before people who don't read the paper comment
1. GPT means general purpose technology or any sort of new technology that has a compounding effect on productivity, not the OpenAI model.
2. Productivity in this case means economic output, not the colloquial definition that means "hard work". If it takes 5 automotive factory workers to assemble a car manually but 2 with industrial automation, then the latter are more productive than the former despite expending equal amounts of effort.
3. The crux of this paper is that existing economic metrics are not able to adequately measure the impact of IP and R&D driven innovations in the larger economy. For example, think about how it took 20-30 years for traditional econometrics to fully gauge the impact of digitization and industrial automation that began in earnest in the 1990s and early 2000s.
> 2. Productivity in this case means economic output, not the colloquial definition that means "hard work".
The colloquial definition doesn't mean “hard work”, it also means you “produce” more for the same amount of time. The difference is how you measure what's being “produced”.
With the “economic output” definition a barista in a posh bar in SF is “more productive” than their counterpart in a popular place in rural Minnesota, because it generates more revenue, even if the later serves twice as many patrons while also keeping the restroom clean (which would colloquially make the later “more productive”).
“Economic output productivity” can also decline if consumer spending do so, not because workers are “less productive” (in the colloquial sense), but because unsold goods or services don't count as “economic output”.
(IMHO overloading things that have a well-defined colloquial term is a very bad habit of economists and it makes things needlessly confusing for laypersons)
Completely adjusting how the business functions to take into account AI is still not on the minds of most businesses. It’s going to require some “creative destruction” (to use the fashionable term) and new companies to really take advantage of this.
You might have two months after NVidia 3090s came out where they were short, but it is nothing like today.
AI companies are intentionally trying to monopolize the supply of inputs needed for R&D. This violates homogeneity of degree 1.
https://lightsight.ai/blog/j-curve (disclosure: my company’s blog)
https://www.financialprofessionals.org/training-resources/re...
Q: The J-dip is where capital stock is just about to overtake investment growth, why should it lag the hype trough where presumably value overtakes interest ?
1. GPT means general purpose technology or any sort of new technology that has a compounding effect on productivity, not the OpenAI model.
2. Productivity in this case means economic output, not the colloquial definition that means "hard work". If it takes 5 automotive factory workers to assemble a car manually but 2 with industrial automation, then the latter are more productive than the former despite expending equal amounts of effort.
3. The crux of this paper is that existing economic metrics are not able to adequately measure the impact of IP and R&D driven innovations in the larger economy. For example, think about how it took 20-30 years for traditional econometrics to fully gauge the impact of digitization and industrial automation that began in earnest in the 1990s and early 2000s.
The colloquial definition doesn't mean “hard work”, it also means you “produce” more for the same amount of time. The difference is how you measure what's being “produced”.
With the “economic output” definition a barista in a posh bar in SF is “more productive” than their counterpart in a popular place in rural Minnesota, because it generates more revenue, even if the later serves twice as many patrons while also keeping the restroom clean (which would colloquially make the later “more productive”).
“Economic output productivity” can also decline if consumer spending do so, not because workers are “less productive” (in the colloquial sense), but because unsold goods or services don't count as “economic output”.
(IMHO overloading things that have a well-defined colloquial term is a very bad habit of economists and it makes things needlessly confusing for laypersons)