Artificial Intelligence
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Taiwan is nearly a world-class leader in the upstream of the LEO satellite supply chain (RF PA, filters, high-frequency PCB), and has decent participation in the downstream (ground terminals, antennas) — but a structural void exists in the hottest new theme of 2025–2026: mid-stream C, Orbital Data Center (ODC) hardware integration.
This is not an accident. It is a structural opportunity window.
In March 2026, Jensen Huang said something on the GTC stage:
"Space computing, the ultimate frontier, has arrived."
This was not a metaphor. In November 2025, US startup Starcloud launched an NVIDIA H100 into orbit (Starcloud-1) and completed the first large language model training session in space. Two months later, on January 11, 2026, Axiom Space launched two orbital data center nodes (ODC Node 1 & 2), connected them to Kepler Communications' optical relay network, and began offering cloud compute services to external customers.
Earth orbit has officially become a new location class for data centers.
This post captures my current engineering thesis across AI systems, space infrastructure, blockchain, and RF validation.
This post is automatically generated for the week starting 2026-03-23.
General-purpose LLMs are powerful, but when it comes to deep analysis in specialized domains, they have two hard limitations: knowledge that lags behind the cutting edge, and factual dilution for niche fields. Take the Polkadot ecosystem as an example — key 2024–2026 developments like Agile Coretime, RegionX, and JAM are either unanswerable by general models, or return outdated information.
The solution is not a bigger model — it's giving the model a structured, trustworthy external knowledge base, then wrapping it with a persona and task prompt. That's the motivation behind my myGPTs.