Blog & Insights

From “What’s the next AI stock?” to “Where’s the next bottleneck, who gets paid, and what would prove us wrong?” Sinclair Huang This essay helps answer four practical questions:- Which AI themes are real constraints rather than just attractive stories? - Who can capture gross margin when a constraint binds? - How long might the bottleneck last before capacity, substitution, or efficiency relieves it? - What evidence would prove the thesis wrong? ...

Why the second AI revolution may be bigger — and riskier — than the firstSinclair Huang AI Infrastructure Notes｜Article 5* Field Note v4 — updated with GTC Taipei and statistical-science reference materials, using public and user-provided sources available as of June 6, 2026.* AI is acquiring three things it never had at scale: a ticker, an agent, and a body. A ticker makes AI liquid. An agent makes AI operational. A body makes AI physical. ...

## COMPUTEX 2026 and Taiwan’s shift from supply chain to co-design and deployment marketplaceAI Infrastructure Notes｜Article 4 Sinclair Huang Field Note v4 — updated with GTC Taipei and statistical-science reference materials, using public and user-provided sources available as of June 6, 2026. I am writing this at a strange distance from Taiwan. While friends in Taipei are celebrating a market that seems to have escaped ordinary scale, I am abroad, watching the same numbers with admiration, unease, and a growing sense that another AI market commentary would not be enough. ...

Product exposure, process-control exposure, and the physical bottlenecks behind the AI capex wave AI Infrastructure Notes | Part 3 Sinclair Huang A reader recently left a comment on my ABF substrate piece that stayed with me. His point was simple: CoWoS and HBM get most of the attention, but substrate materials often sit below the level where many equity models even begin. I think that observation captures a broader problem in AI infrastructure analysis. ...

Why CPO is not an optics story — it is a process-integration story. AI Infrastructure Notes | Part 2 Sinclair Huang Everyone says AI needs more bandwidth. That part is true. As AI clusters scale from thousands of accelerators to tens of thousands, and then toward million-GPU-scale systems, the network stops being a background layer. It becomes part of the compute fabric itself. Copper reaches its distance, power, and signal-integrity limits. Optical interconnect moves closer to the switch ASIC. Co-packaged optics becomes the logical next step. ...

** In a world of infinite content and scalable intelligence, the scarcest resource may no longer be intelligence itself — but the ability to truly see another human being, and to be seen in return.** By Sinclair Huang I walked into a bookstore — and realised something uncomfortable A few days ago, I walked into a bookstore. Surrounded by shelves of books — many of them thoughtful, deeply human, and difficult to summarise — I had a quiet realisation: ...

Everyone Is Betting on AI — But Almost No One Asks: Where Are You Standing?The AI boom is real. The harder question is where value, risk, and leverage accumulate inside the stack. Position matters more than opinion. Over the past few weeks, I have been thinking about AI through a different question: Why can the same AI cycle feel so powerful in markets, yet so uncertain in daily life? My own view is more optimistic than pessimistic. ...

Work, ownership, and the new architecture of economic security By Po-Sung(Sinclair) Huang For decades, people believed that working hard was enough. In the AI era, that assumption is quietly breaking. Not because work disappears, but because ownership matters more than ever. In the AI era, relying on labour income alone is no longer a neutral choice. It is an active form of risk. That sentence may sound harsh. But it captures a structural shift that many people can already feel, even if they do not yet have the language for it. They feel it in markets. In career anxiety. In the fear of being left behind by a technology wave they did not ask for, do not fully control, and may not directly benefit from. ...

From dBase and enterprise systems to the internet revolution and generative AI, I have come to see AI not as a sudden break, but as the latest step in a long slope of automation now reaching human cognitive work itself.* By Po-Sung(Sinclair) Huang I did not decide to write this essay because AI suddenly became fashionable. It came out of two images that collided in my mind. One was a group of younger people trying to imagine new ventures built around AI. The other was the story of a father facing a rare disease so obscure it seemed to leave almost no path forward, and yet continuing, late into the night, to search for a way through with the help of computation, search, and structured reasoning. ...

From compute bottlenecks to industrial consequences — where value may actually concentrate through 2030 Series: AI Compute Supply Chain | Part 5 of 5 Author:* Po-Sung(Sinclair) Huang |For the past four articles in this series, I have written about CoWoS, HBM, ABF substrates, SEC filings, and the fault lines that could eventually crack today’s moats. On the surface, that may look like a semiconductor series. It is not. What these articles really reveal is something larger: AI is no longer just a software story, and no longer just a model race. It is becoming an industrial system — one that depends on power, cooling, capital expenditure, advanced packaging, memory bandwidth, substrate materials, qualification cycles, and the physical discipline of manufacturing scale. ...