The Daily Brief by ZERODHA raises one of the most important issues of our times —What really separates US and Chinese AI—and,explains similarity between both AI ecosystems.
I may like to the below extracts Mr.Sangeet Pual Chowdhary on this:
# The US is betting on intelligence. China is betting somewhere else!
# The US frequently frames its competition with China as an AI race, similar to the space race it ran with the USSR. The idea of a race was triggered around a year ago with the launch of DeepSeek. Ever since, much of the US media has been fascinated with the idea of the US winning the AI race against China.
# Ironically, it isn’t much of a race if the US is the only one running it.
# The American ‘AI race’ is framed around who will build the smartest models, as if superior intelligence alone decides the future.
# China’s strategy reveals a different understanding of the game altogether.
# It is not trying to win AI at all. It is betting that intelligence will become abundant, and that power will flow instead to whoever can reliably turn intelligence into economic value.
This was a really engaging piece, and the way you used Ren Zhengfei’s quote to frame the two “AI philosophies” made the whole topic feel very accessible. It does a nice job of contrasting the US “frontier, closed, NVIDIA-heavy” model with China’s more resourceful, open and applied approach.
One thing that left me curious, though, was the hard economics behind that contrast. You mention that AI capex made up around 40% of US economic growth and that other sectors look relatively stagnated, which is a powerful point. When set against the broader data, the imbalance looks even sharper: over the past decade, US private AI investment is just under half a trillion dollars, roughly four times China’s ~120 billion USD, yet there isn’t a matching surge in US corporate profits from AI just yet.
On the China side, you highlight how models like DeepSeek are quietly getting embedded into cars, phones and hospitals, and that feels directionally right. Recent official numbers suggest China’s AI industry has already crossed roughly 900 billion yuan (about 127 billion USD) in annual revenue, spread across more than 5,000 AI-related firms and growing at over 20% a year, which hints at a fairly tight link between investment and real‑world commercialization. If you roughly compare cumulative private investment (~120 billion USD) with that current annual industry size, China’s investment-to-revenue ratio starts to look surprisingly healthy.
All of that makes your central point about “convergence” even more interesting. The US seems to be coming from a “build frontier infrastructure first, figure out profits later” mindset, while China seems to have started from “embed AI into the existing economy first, then push for the frontier.” It might be fascinating in a future edition if you revisited this topic with a couple of simple charts or numbers on :
1. how much AI capex is actually showing up as disclosed AI‑driven revenue in US companies, and
2. how much of China’s AI growth is inside traditional sectors versus pure‑play AI firms.
The current narrative is already very strong; a little more of this kind of empirical framing could make it an even more grounded and useful reference for readers trying to understand where the “AI boom” is real business and where it is still mostly infrastructure and hope.
Yours is a very fair characterization, and both those questions aren't something we can address in the "Who Said What" format. We did a couple of pieces on the first question, showing how wild the imbalance is.
But the second question is hardly something we've covered. Before we can even tackle Chinese LLMs alone, we'd love to look at their robotics industry, which has indeed integrated strongly with its manufacturing base. Will need to spend some time on it and devote a whole Daily Brief episode on it :)
Yep! I personally think that AI will be like any other technology when it comes to production and commercialization/adoption. But the commercialization itself will be like no other technology in history.
The Daily Brief by ZERODHA raises one of the most important issues of our times —What really separates US and Chinese AI—and,explains similarity between both AI ecosystems.
I may like to the below extracts Mr.Sangeet Pual Chowdhary on this:
# The US is betting on intelligence. China is betting somewhere else!
# The US frequently frames its competition with China as an AI race, similar to the space race it ran with the USSR. The idea of a race was triggered around a year ago with the launch of DeepSeek. Ever since, much of the US media has been fascinated with the idea of the US winning the AI race against China.
# Ironically, it isn’t much of a race if the US is the only one running it.
# The American ‘AI race’ is framed around who will build the smartest models, as if superior intelligence alone decides the future.
# China’s strategy reveals a different understanding of the game altogether.
# It is not trying to win AI at all. It is betting that intelligence will become abundant, and that power will flow instead to whoever can reliably turn intelligence into economic value.
This was a really engaging piece, and the way you used Ren Zhengfei’s quote to frame the two “AI philosophies” made the whole topic feel very accessible. It does a nice job of contrasting the US “frontier, closed, NVIDIA-heavy” model with China’s more resourceful, open and applied approach.
One thing that left me curious, though, was the hard economics behind that contrast. You mention that AI capex made up around 40% of US economic growth and that other sectors look relatively stagnated, which is a powerful point. When set against the broader data, the imbalance looks even sharper: over the past decade, US private AI investment is just under half a trillion dollars, roughly four times China’s ~120 billion USD, yet there isn’t a matching surge in US corporate profits from AI just yet.
On the China side, you highlight how models like DeepSeek are quietly getting embedded into cars, phones and hospitals, and that feels directionally right. Recent official numbers suggest China’s AI industry has already crossed roughly 900 billion yuan (about 127 billion USD) in annual revenue, spread across more than 5,000 AI-related firms and growing at over 20% a year, which hints at a fairly tight link between investment and real‑world commercialization. If you roughly compare cumulative private investment (~120 billion USD) with that current annual industry size, China’s investment-to-revenue ratio starts to look surprisingly healthy.
All of that makes your central point about “convergence” even more interesting. The US seems to be coming from a “build frontier infrastructure first, figure out profits later” mindset, while China seems to have started from “embed AI into the existing economy first, then push for the frontier.” It might be fascinating in a future edition if you revisited this topic with a couple of simple charts or numbers on :
1. how much AI capex is actually showing up as disclosed AI‑driven revenue in US companies, and
2. how much of China’s AI growth is inside traditional sectors versus pure‑play AI firms.
The current narrative is already very strong; a little more of this kind of empirical framing could make it an even more grounded and useful reference for readers trying to understand where the “AI boom” is real business and where it is still mostly infrastructure and hope.
Hey Rajesh, thanks for the insightful comment!
Yours is a very fair characterization, and both those questions aren't something we can address in the "Who Said What" format. We did a couple of pieces on the first question, showing how wild the imbalance is.
But the second question is hardly something we've covered. Before we can even tackle Chinese LLMs alone, we'd love to look at their robotics industry, which has indeed integrated strongly with its manufacturing base. Will need to spend some time on it and devote a whole Daily Brief episode on it :)
https://hai.stanford.edu/ai-index/2025-ai-index-report
Yep! I personally think that AI will be like any other technology when it comes to production and commercialization/adoption. But the commercialization itself will be like no other technology in history.