I went long $AMD at $4.20 a decade ago because I believed chiplets would become the foundation of modern compute. They did. $IBRX gives me the same feeling today, but in biotech. Anktiva isn’t just a fusion protein complex. It’s an operating system for the human immune system.

New technical papers recently added to Semiconductor Engineering’s library #semiconductor# #3DIC# #chiplets# #BEOL# #thermalmodeling# #semiEDA# #neuromorphiccomputing# #LLMs#

As AI chips move to stacked, chiplet-based architectures, EDA vendors are reworking mature tools for cross-domain analysis, faster exploration, and agentic AI assistance. #semiconductor# #semiEDA# #3DIC# #AgenticAI# #chiplets#

The difficulty in building a package digital twin goes beyond creating accurate electrical, thermal, or mechanical models. #semiconductor# #advancedpackaging# #digitaltwins# #chiplets# #semiocnductormanufacturing#

$AMD at the Citi Global TMT Conference “We haven't given a ton of details yet, but we do have some of our own internal silicon ambitions for ultra-low-latency inference that would fit into our architecture via chiplets.” The Taalas acquisition and the Cerebras partnership are just $AMD’s baby steps into ultra-low-latency inference The goal is to develop this silicon in-house going forward, and the trend we’ll likely see is increasingly specialized ASICs designed for specific workloads

Agentic AI is changing what the data center needs from the CPU. At SEMICON Taiwan, CK Tseng shared how Arm is helping the ecosystem scale AI infrastructure through more efficient CPUs, custom silicon, chiplets and tighter system integration.

$MU $SKHY $DRAM 20 HBM Cubes. 1 compute die. Find the Waldo. OpenAI ASIC patent tells you exactly where memory demand is headed. "Non Adjacent Connection of High Bandwidth Memory Chiplets, I/O Chiplets, and Compute Chiplets Through Embedded Logic Bridges."

Check out the latest blog, by Raghu Shankar, “Developing AI-native Automated Virtual Chiplet Eco-systems: Shift Left, Shift Up, and Shift Out to accelerate Chiplet adoption.” Key Takeaways: · SIPs with 2.5D and 3D chiplets deliver 10x functionality, modular dies, higher yields, lower cost, and cross-generation reusability. · Chiplet adoption needs clear value proposition, demand sizing, and vendor profitability proof to justify supply-side investments across products and generations. · Shift left: Move evaluation to planning and design space exploration for early PPAC estimates, lowering risk, cost, and time to decision. · Shift up: Focus at the architecture layer, abstract physical and protocol details, use HLS synthesis, simulation, emulation, and prototyping. · Shift out: Expand pool of buyers and sellers to maximize explorations. · Develop AI native virtual ecosystem: Automate chiplet interop testing with virtual prototyping. Read the full story here: And attend the panel session on this topic at the OCP Global Summit as part of the Server/Open Chiplet Economy track on October 15, 2026 in San Jose, CA. Learn more and register here: