To me $NAUT is a classic ALC giga-asymmetry Chiplets for $AMD back in 2014 projected over a decade plus = trillion dollar company Iterative mapping today for $NAUT is the same deal Odds of going to zero, but the asymmetry is beautiful

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.

A decade ago, I went long $AMD at $4.20 because I saw chiplets becoming the foundation of modern compute. That’s exactly what happened. Today, $IBRX gives me the same feeling in biotech. I see Anktiva as far more than a fusion protein complex. 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