TFHK Commentary: How Should We Understand the Current Correction in AI Hardware? The market is always right. Changes in stock prices inevitably reflect the new variables the market is currently pricing in. Even as long-term bulls on the AI industry, we need to understand the core concerns driving this correction in AI semiconductor stocks. The current market bears a striking resemblance to last autumn and winter. Following OpenAI’s large fundraising round, industry conditions were very strong, yet stocks continued to trade sideways. Market participants spent every day debating CapEx, ROI, valuations, and financing—much like they are doing now. The conclusions from this quarter’s earnings reports remain overwhelmingly positive. GCP grew by 80%, the ROI of cloud investment was validated, Intel delivered a significant beat, and ASML, TSMC, and Intel raised their order or CapEx outlooks. Presumably, these companies also saw extremely strong downstream forecasts, giving even the most conservative players in the supply chain the confidence to make aggressive bets. Had this information emerged in May or June, semiconductor stocks would almost certainly have surged. Now, however, every earnings release has instead become an opportunity for bears to reassess valuations and the long-term investment thesis. What we may be seeing is that the AI market is no longer in the “AI Summer” of May and June. The same positive developments now provide less support to share prices. Take GCP’s 80% growth as an example. Previously, the market’s first reaction would have been: “AI demand has exceeded expectations—the catalyst has arrived.” Now, the first response is: “So what? What about 2028? Can OpenAI become profitable? For how many more years can GPU prices keep rising? Margins are rising again, financing costs are increasing, and the entire CapEx thesis needs to be repriced.” In essence, the market has shifted from trading the growth of AI CapEx to trading its sustainability and ROI. Market sentiment, as we perceive it, has already become extremely bearish. Even long-term bulls are beginning to question whether AI semiconductor stocks can continue to rise, and we are hearing almost no calls for new highs. When the market shifts from looking for further upside to searching for additional downside risks, it usually means that pessimistic expectations have already been largely priced in. Nevertheless, we have no doubts about the fundamentals. We also believe that, ultimately, facts determine stock prices. So what would send these stocks higher again? Under the framework outlined above, additional capital-spending plans alone will no longer be enough to convince the bears. What is needed is validation of a new demand curve. The most powerful and direct catalyst would be the emergence of a blockbuster product. If “Coding 1.0” proved that AI can improve developer productivity, then “Coding 2.0” must demonstrate that AI agents can genuinely replace part of the software development process. Once new productivity use cases are validated, the market’s concerns about AI ROI may be redefined, and AI infrastructure spending will once again be viewed as “productivity investment” rather than a “cost.”