Episode summary
The AI Gap Is Closing | Jason Hsu on China, Momentum Crashes and the S&P’s Seven-Stock Bet
Excess Returns
· · 55 min · Guests: Jason Hsu
Summary
Jason Hsu argues that the AI race between the US and China is already a global competition, not one that can be solved by regulating only American firms. He says Chinese model quality has closed to roughly parity with the US, and that if the US slows down, Chinese firms would simply leapfrog ahead. In his view, the real policy question is safety coordination between the two powers, because “the genie's out of the bottle.”
He also argues that the economics of AI may favor hardware, energy, and integrators more than the model builders. China, he says, has structural advantages in energy sourcing, grid efficiency, and open-source models, which make it easier to push AI deployment while monetizing hardware and power. Over time, he expects model differences to matter less, while application builders and infrastructure providers capture more of the rent.
Turning to markets, Hsu says China remains fertile ground for factor investing because of its retail-heavy trading base and large, inefficient market structure. He contrasts that with the S&P 500, which he says is increasingly concentrated in a few AI-linked names, making passive investors less diversified than they assume. He remains constructive on factors and machine learning, but says investors should be careful about where they are really taking concentrated thematic risk.
Key takeaways
- Hsu says China is now effectively on par with the US in AI model development, with open-source models eroding any durable software advantage.
- He expects most AI economics to accrue to hardware, energy providers and application integrators rather than frontier model vendors.
- He argues that Chinese open-source models and energy infrastructure give China a real competitive edge in scaling AI.
- Hsu warns that the S&P 500 is increasingly a seven-stock bet, so passive investors may be far less diversified than they think.
- He says factor investing still works in China because retail dominance creates more mispricing and more behavioral alpha opportunities.
- He believes momentum crashes are normal and should be diversified with value rather than timed.
Notable quotes
“the genie's out of the bottle. You can't put it back in in the following sense, right”
“in equilibrium most of the value is not going to be in the models”
How the episode opens
Jason, hello and welcome back to Excess Returns. Hi Justin. Hi Jack.
You are founder and chief investment officer at Railant Global Adviserss, a quantitative firm focused on investing around the world in both developed and emerging markets before launching Railant. You were co-founder of Research Affiliates. I'm not sure if it carries that name anymore given what's transpired with the with with the firm, but you and Rob Arnot were sort of instrumental and at the forefront of turning factor based approaches into investable products and investment strategies.
And I think today, you know, we've had you on a couple times to talk about your investment approach and how you're deploying these factor-based strategies around the world. And we'll get into some of that. But we wanted to start by I think connecting your experience and knowledge into sort of talking about the global race of AI at least to start and then we can get into factor-based investing sort of the risks and opportunities in different areas and different markets including Asia and China.
And then I think bridging the gap which you do a great job at at sort of talking about what is working in research and academic worlds into portfolios that work for the real world and in in actual investment strategy. So thanks again for doing this. Third time's a charm.
You're always welcome here. But I think to start we wanted to ask you about your reaction to the anthropic CEO's letter over the weekend. There's this sort of push and pull happening in AI right now where and I'm not going to rehash it all but there's safety concerns.
Some are calling for more regulations. PE some of these CEOs are saying we need to slow down. We need to put ours in place.
From the episode’s captions: roughly the first two minutes, lightly cleaned. Keep watching on YouTube →
Topics
- us-china ai race
- ai spending economics
- chip restrictions and domestic capability
- momentum crashes and value cycles
- s&p 500 concentration risk
Companies and tickers mentioned
- Rayliant Global Advisors
- Research Affiliates
Watch the episode
Summary, takeaways and quote selection by Octagon. Quotes are short excerpts; the full conversation is in the episode.
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