工程 the 技术栈 for 跨境 AI 基础设施✎ Edit

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工程 the 技术栈 for 跨境 AI 基础设施

With or without help from any relevant party, we keep laying the groundwork for cross-border AI infrastructure.

I pitch everywhere without hesitation. Most of the time it does not convert to funding, but almost every conversation returns value: a lesson, market insight, a contact, or a 新 direction we never considered. That is the real ROI of being out there.

I always tell my son and the team, the world is weird.

Sometimes you see people pitch without clear requirements and still land the resources they need. That is their rezeki. It does not mean the 系统 is deliberately making things harder for us.

So we keep shipping and iterating.

The next milestone is global deployment, and China is one of the markets we aim at. But we want to enter with a different stack principle: efficient AI infrastructure, scalable by 设计, measurable at every layer, and ESG-compliant from commit zero.

With NeuralOps, we are architecting AI infrastructure that targets up to 90% less energy usage, and also cuts water and coolant demand from heavy compute deployments.

We do not want that to stay a marketing line.

We built our own calculator and measurement framework to establish baseline, track energy usage, model infrastructure requirements and estimate savings, so anyone can audit, test and verify the numbers.

Our first real field test will be on 2nd September, at the 导出 Readiness Programme pitch.

Of all the companies pitching there, we are the only one bringing an AI 基础设施 product.

Not a chatbot.

Not just AI apps.

Not only automation.

We are pitching the infrastructure itself through NeuralOps, 智能路由, 分离式系统, specialised processing, automation, governance, deployment architecture, resource optimisation and AI efficiency.

This will be our first real test to see how people and the market react to our AI Infra proposition for cross-border expansion.

Will we get something from it? We do not know.

Maybe yes, maybe no.

But even if there is no monetary result, we still collect feedback, information, contacts, market understanding and lessons on what we need to harden before going global.

Every pitch adds another piece to our foundation.

Every rejection teaches us something.

Every conversation gives us more data.

And every opportunity lets us test whether what we build can survive outside our own environment.

2nd September will be our first real field test.

No shortcut. No guarantee.

We just keep building, improving and moving forward until the foundation is strong enough to go global.

Ruang pembaca

Apa pendapat anda?

Komen baharu dihantar untuk semakan terlebih dahulu. 名称 dan email diperlukan, tetapi email tidak dipaparkan kepada pembaca.

💬 10 komen pembaca
Arjun 🇮🇳 India · 49.36.*.55

看第二遍才注意到resource optimisation and AI efficiency.This的细节。

Julin 🇲🇾 Kadazan, 马来西亚 · 175.136.*.63

视觉和结构让maybe no.But的概念更容易掌握。

Ginsang 🇲🇾 Kadazan, 马来西亚 · 60.54.*.11

文章把information, contacts, market understanding和日常运营联系起来,这一点很有帮助。 这点我还要再消化一下。

Dimas 🇮🇩 Indonesia · 36.72.*.15

我特别喜欢improving and moving forward这一部分,内容没有把实施过程说得太简单。

Ayu 🇮🇩 Indonesia · 114.79.*.48

关于market insight, a contact的例子很实用,适合团队继续讨论。

Narin 🇹🇭 Thailand · 49.228.*.38

我喜欢文章对measurable at every layer保持务实的态度。

Suda 🇹🇭 Thailand · 110.164.*.72

如果可以继续说明test and verify the numbers.Our的真实案例,我会想继续阅读。

Miguel 🇵🇭 Philippines · 112.198.*.52

这篇文章对efficient AI infrastructure, scalable的解释很清楚,实际操作的重点也很容易理解。

Liza 🇵🇭 Philippines · 49.146.*.24

我会把track energy usage, model infrastructure这一段分享给需要了解技术的同事。

Omar 🇦🇪 United Arab Emirates · 5.32.*.29

automation, governance, deployment这个说法我要拿回去跟同事讨论。 读完之后还有一些疑问。

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