8 posts tagged with "ai"

myGPTs​

• Jamia: about Polkadot & JAM
• Spacesharks: about SpaceTech

這篇是我開始整理各種 "Claw" 工具時的第一份研究筆記。重點不是追熱點，而是先把堆疊分清楚：哪些是官方可驗證的事實，哪些是社群踩坑經驗，哪些目前只能當作待驗證線索。

截至 2026-05-24，我會把 Claw 生態先拆成三層來看：

• OpenClaw：個人 AI assistant / agent 的應用層，負責聊天、channels、tools、workspace、skills。
• NemoClaw：NVIDIA 做的 OpenClaw reference stack，把 OpenClaw 放進更可控的 OpenShell sandbox，補上 onboarding、policy、inference routing 與 lifecycle 管理。
• OpenShell：底層 sandbox / gateway / policy runtime，真正處理隔離、網路出口、檔案系統與推論路由。

接著 上一篇 Claw 堆疊筆記 之後，今天把 NVIDIA Agent Challenge 2026 的參賽計畫「Spacesharks Mission Desk」做了一次重要的重整。

題目沒換，stack 沒換，但我把這個 agent 要證明什麼 重寫了一次。

原本的版本是「把現有 Jamia / Spacesharks GPT 移植到 Nemotron stack」。今天的版本是：

一個低成本、多模型、能拿出證據、可以連跑 24 小時的衛星營運 copilot — 它的可信任性不是來自最大的模型，而是來自一個被刻意設計過的 trust stack。

這篇筆記紀錄這次重整的原因、四層信任架構，以及我為什麼把 scope 鎖到只有四個 ingestion source。

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.

Summary Prediction (Next Week)​

• Macro baseline: neutral
• US equities (S&P 500 / Nasdaq / Dow): neutral
• Crypto (BTC / ETH): neutral

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.