Adrian Mitchell
I focus on advanced semiconductor packaging, with particular attention to 2.5D integration, CoWoS-type architectures, high-bandwidth interconnects, and the packaging requirements of AI accelerators. My research examines how packaging technology is evolving as computing performance increasingly depends on integrating processors and high-capacity memory within a single system. I write for this website because advanced packaging has become a major constraint and opportunity in high-performance computing. As AI accelerators require greater memory bandwidth and larger system-level integration, packaging capacity and manufacturing technology have become increasingly important. My research follows CoWoS-related capacity, silicon interposers, advanced substrates, HBM integration, packaging yields, and customer demand. I also examine how packaging investment affects semiconductor production schedules and the availability of AI computing hardware. I monitor developments across foundries, OSAT companies, substrate suppliers, equipment manufacturers, and materials providers. My goal is to explain how advanced packaging fits into the broader semiconductor supply chain and how packaging technology influences AI infrastructure growth.
Advanced packaging analyst focused on CoWoS, 2.5D integration, HBM integration, interposers, packaging capacity, yields, and AI accelerator demand.
Adrian Mitchell is an advanced packaging analyst specializing in 2.5D integration, CoWoS-related technologies, and the packaging architectures used by high-performance AI accelerators.
Adrian studies the integration of processors and HBM, silicon interposers, advanced substrates, packaging capacity, and manufacturing yields. His research examines why packaging has become increasingly important as AI systems require higher memory bandwidth and greater system-level integration.
He follows investment and capacity expansion across foundries, OSAT providers, substrate manufacturers, equipment suppliers, and materials companies. Packaging bottlenecks can influence the availability and production schedule of advanced computing products, making capacity an important part of his research.
Through his articles, Adrian explains the technical and market developments surrounding advanced packaging and examines how CoWoS-type technologies, HBM integration, and packaging investment are reshaping the semiconductor supply chain.
His Articles
Micron’s $1.8B PSMC Acquisition: Inside the Taiwan DRAM Capacity Land Grab
Micron’s $1.8 billion Taiwan deal is not an acquisition of PSMC itself. It is the purchase of PSMC’s P5 manufacturing site in Tongluo, Miaoli County—a transaction that gives Micron existing cleanroom infrastructure and a route to expand advanced DRAM production faster than starting entirely from scratch.
Semiconductor ETF Flows: $9.19B Net Inflow in One Month
A hypothetical $9.19 billion net inflow into semiconductor ETFs over a single month would be more than a headline statistic. It would represent a meaningful shift in investor positioning toward one of the most important sectors in the global technology economy. Semiconductor ETFs sit at the intersection of artificial intelligence, cloud computing, automotive electronics, smartphones, industrial automation, memory, advanced manufacturing, and high-performance computing. When billions of dollars move into these funds within a relatively short period, the flow itself can become part of the investment story.
Auto Chip Supply-Demand Reversal: From Extreme Shortage to Structural Surplus
Only a few years ago, automakers around the world were halting production lines because they could not secure enough chips. Waiting lists for vehicles stretched out, component allocations were rationed, and procurement teams scrambled to find even small volumes of critical microcontrollers and power devices. Today, the picture looks very different. In multiple auto chip categories, supply has not just caught up with demand—it has overshot. What was once an extreme shortage is increasingly turning into a structural surplus.