To The Moon

1. Live Review Introduction

Tiger Brokers livestream featuring Ross Dong, Founding Partner at Morning Cloud Asset Management, specializing in macro trading and U.S. equities. A former equity trader at firms including J.P. Morgan and KCG, Ross holds a degree in Applied Mathematics from Columbia University.

In this section, Ross explores where the next AI opportunity could emerge if the first wave of the AI trade was dominated by GPUs and hyperscalers.

Ross believes the AI value chain is broadening beyond chips into power, infrastructure, advanced manufacturing, cybersecurity, China tech, and robotics. His key message: the next AI winner may not look like a traditional AI stock.

Disclaimer: All views and company examples reflect discussion by the livestream guest and are provided for educational purposes only. They are not investment recommendations.

Catch up on the full recap series

• Live Recap 1: Why Ross Cut AI Exposure Before the Sell-Off

• Live Recap 2: Rate Cuts, Jackson Hole and the U.S. Market Setup

• Live Recap 3: AI Has Burned Billions — Are the Returns Finally Showing Up?

2. The AI Trade Is Expanding Beyond Chips

The first stage of AI spending centred on GPUs, memory and data centres.

Ross believes the next phase could extend further down the infrastructure chain:

Compute → Data Centres → Power → Grid Infrastructure → Physical Infrastructure

As AI capacity expands, these supporting industries could capture a larger share of investment.

3. Power and Energy Could Be the Next Bottleneck

Ross sees power and energy infrastructure as one of the more underappreciated areas of the AI ecosystem.

AI data centres require enormous amounts of reliable electricity, increasing demand for:

• Power generation

• Transmission and distribution

• Grid infrastructure

• Transformers

• Data-centre infrastructure

During the Q&A, Ross mentioned $Vistra Energy Corp.(VST)$ and $Constellation Energy Corp(CEG)$ and also expressed interest in nuclear-related opportunities.

His thesis:

AI cannot scale on chips alone — it also needs energy.

Industrials exposed to power generation and infrastructure could therefore become indirect AI beneficiaries as well.

4. $Taiwan Semiconductor Manufacturing(TSM)$ Remains a Critical AI Bottleneck

Ross also highlighted TSMC because of its leading position in advanced semiconductor manufacturing, including 2nm and 3nm production.

Chip designers may gain or lose market share, but many still depend on advanced foundry capacity.

That makes semiconductor manufacturing a different type of AI exposure from simply choosing which GPU designer will win.

5. Robotics Has Potential — But It Is Earlier

Ross is optimistic about robotics, including $Tesla Motors(TSLA)$ Optimus, robotaxis and Waymo, but believes mass adoption remains further away.

Today's AI excels at model intelligence.

Robotics requires spatial intelligence — understanding and safely interacting with the physical world.

Tasks such as navigating spaces, handling objects and performing household work remain significantly harder.

For Tesla, Ross believes the long-term story could increasingly shift toward:

Software + Robotaxi + Optimus

rather than relying mainly on vehicle sales.

6. China Could Become an AI Catch-Up Trade

Ross also sees potential in Chinese technology.

He noted that global portfolio managers remain relatively underweight China tech, while China's share of the global AI ecosystem remains smaller than that of the U.S.

His long-term view is that AI competition is increasingly centred around:

United States + China

Ross highlighted companies including $TENCENT(00700)$ , $NTES-S(09999)$ , $BABA-W(09988)$ , $JD-SW(09618)$ , $TRIP.COM-S(09961)$ and $BIDU-SW(09888)$ , arguing that some trade below their own historical valuation ranges.

He also expects China's domestic AI-chip ecosystem to grow as local GPU and ASIC alternatives gradually replace some foreign supply.

At the same time, Chinese technology companies are increasing AI CAPEX, supporting a broader domestic ecosystem:

Models → Chips → Cloud → Data Centres → Applications

7. AI Could Benefit Financials and Cybersecurity Too

Ross believes AI exposure should not only be measured by who sells AI products.

It also matters how AI changes a company's economics.

For financial firms such as $JPMorgan Chase(JPM)$ , $Goldman Sachs(GS)$ and $Morgan Stanley(MS)$ , AI could improve efficiency across research, data processing and operations.

Cybersecurity could benefit for a different reason: more powerful AI may also create more sophisticated digital threats, increasing demand for security solutions.

The broader point:

Some of AI's biggest beneficiaries may be companies using AI rather than selling it.

8. $Gold - main 2612(GCmain)$ and $Silver - main 2609(SImain)$ Reinforce Ross's Cycle Framework

Ross also returned to his broader investment principle: everything moves in cycles.

His fund built gold and silver positions from late 2024 into early 2025, exited after a sharp parabolic rise, and later became interested again after prices corrected.

His lesson applies across commodities, semiconductors and AI:

A strong asset can become a poor trade when price runs too far ahead of fundamentals — and become attractive again after expectations reset.

9. What AI May Not Replace

Ross ended with a broader observation.

Even if AI eventually surpasses humans across many cognitive tasks, he believes human connection, emotion and relationships will remain difficult to replace.

As AI becomes more powerful, those uniquely human elements may become even more valuable.

Closing Takeaway

The first AI trade was dominated by GPUs and compute.

Ross believes the next phase could broaden into:

Power → Infrastructure → Advanced Foundries → Cybersecurity → China Tech → Robotics

His framework is not about chasing every company linked to AI.

It is about finding areas where demand is still growing but valuations and expectations have not already moved too far ahead.

The next major AI opportunity may therefore come from a business investors do not traditionally think of as an AI company.

10. Post-Event Resources

Viewers can follow @Ross_Macro_Trading on the Tiger Community, his YouTube channel TMI Partner, or his X account, Ross Dong. More of his market views and research are also available through his official website, tmipartner.com.