The narrative that Malaysia has already "won" the regional data center race—particularly in Johor—is a premature celebration. While the federal government eyes massive investment figures, local communities are beginning to realize that these monolithic structures often take more than they give.
Subject: Announcing the Strategic Rebranding of PCDS to SAIS (Sovereign Artificial Intelligence Spaces)
Malaysia has positioned itself as Southeast Asia's rising digital capital, attracting billions in investments from hyperscalers like Microsoft, Google, ByteDance, and others. From 2021 to mid-2025, authorities approved over 140 projects worth nearly RM144 billion (around USD 34 billion), with Johor emerging as the epicenter—home to dozens of operational, under-construction, and approved facilities.
If you have your OpenClaw working 24/7 using frontier models like Opus, you're easily burning $300 a day.
That's $100,000 a year.
I have 3 Mac Studios and a DGX Spark running 4 high end local models (Nemotron 3, Qwen 3.5, Kimi K2.5, MiniMax2.5). They're chugging 24/7/365. I
MiniMax-M2.5 went fully open source and it’s basically Claude Opus performance but 95% cheaper..
it scores 80.2% on SWE-bench verified. It's 3x faster than the industry leaders.
4 useful use cases:
1. Build interactive prototypes
http://x.com/i/article/2015708264906768384
Running OpenClaw locally? Do it safely.
This walkthrough shows how to run it inside Docker Sandboxes with Docker Model Runner:
- Isolated microVM
- No exposed API keys
- Controlled network access
- Fully private, local AI setup
Secure agent workflows in ~2 commands.
Read →
17,000 tokens per second!! Read that again!
LLM is hard-wired directly into silicon. no HBM, no liquid cooling, just raw specialized hardware. 10x faster and 20x cheaper than a B200.
the "waiting for the LLM to think" era is dead. Code generates at the speed of human thought.
