Neoclouds: Redefining Cloud for the AI Era

Inside GMI Cloud’s Journey and the Future of AI Infrastructure

2025-05-02

Why managing AI risk presents new challenges

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The difficult of using AI to improve risk management

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How to bring AI into managing risk

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Pros and cons of using AI to manage risks

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Benefits and opportunities for risk managers applying AI

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This article is a translated and lightly edited summary of the Tech Wave podcast conversation, prepared by GMI Cloud for clarity and readability.

Introduction: A New Cloud for a New Era

As artificial intelligence (AI) accelerates across industries, traditional cloud architectures are falling behind. The AI era demands more: infrastructures that are faster, specialized, flexible, and AI-native by design.

This gap has sparked the rise of a new generation of cloud providers: Neoclouds.

In a recent episode of Tech Wave, one of the top Mandarin-language tech podcasts hosted by Harry, a tech creator with over 430,000 followers, GMI Cloud founder and CEO Alex Yeh shared firsthand insights on this evolution.


Their conversation went beyond technical trends; it became a story of resilience, opportunity, and the future of cloud computing itself.

Meet the Platform: Tech Wave and Harry

Tech Wave is a leading podcast for Mandarin-speaking audiences seeking clear, analytical discussions on emerging technologies.

Hosted by Harry, a former McKinsey & Company analyst turned tech influencer, Tech Wave focuses on breaking down complex ideas into accessible insights.


With a loyal, fast-growing following, it’s the perfect stage for a conversation about the future of cloud.

From Bitcoin Mines to AI Infrastructure: GMI Cloud's Origin Story

Alex Yeh’s entrepreneurial path wasn’t cloud-native; it started underground in Bitcoin mining farms.

Three years ago, Alex was a partner at Taiwan’s largest crypto fund, overseeing a mining operation in Inner Mongolia.
Then, overnight, everything changed:

"I woke up and saw the hashrate drop to zero," Alex recalled. "China had banned Bitcoin mining without warning."

Forced to pivot, Alex flew to the U.S. trying to salvage operations.
While rebuilding, he noticed a new wave of demand for AI training and inference compute, not mining.

"I fell into AI like Alice into the rabbit hole," he joked.

Rather than give up, Alex assembled a team including engineers from Google X and built three new data centers across Taiwan and Thailand within ten months, GMI Cloud was born.

Notably, many peers tried to pivot into hosting general virtual machines, but Alex had a different vision: GPU infrastructure optimized specifically for AI builders.

What Exactly Is a Neocloud?

Traditional cloud providers like AWS, Azure, and GCP were built for general-purpose computing such as websites, storage, and enterprise apps.

But AI workloads have radically different needs:

  • Massive parallel GPU processing

  • High throughput inference and low-latency response

  • Fine-grained optimization for speed, memory efficiency, and cost

"Neoclouds aren’t just about renting GPUs," Alex explained. "They deliver AI-native infrastructure with the flexibility, modularity, and speed today's AI companies demand."

Neoclouds like GMI Cloud are:
✔️ Built AI-first, not retrofitted after the fact
✔️ Modular and hybrid-ready, deployable on cloud, on-premises, or both
✔️ Cost-optimized, especially for inference-heavy workloads
✔️ Highly responsive, tuned to evolving customer needs

Neoclouds are infrastructure built from scratch to power AI’s unique compute and deployment challenges, a full-stack rethink.

GMI Cloud’s Vision: The Shopify of AI

Rather than replicate traditional hyperscaler models, GMI Cloud is creating a modular, customizable cloud platform made for AI practitioners.

🔹 Hardware Layer: Latest NVIDIA H100 and B200 GPUs tuned for AI acceleration.
🔹 Cluster Engine: Smart orchestration and virtualization built for AI workloads.
🔹 Inference Engine: Direct API access to fine-tuned models like DeepSeek R1, Llama 3, Qwen, and more.

"We don't lock you in," Alex emphasized. "You can deploy our stack anywhere, your own servers, other clouds, or hybrid. We give you the keys, not just rent you a room."

GMI’s modular approach directly addresses enterprise concerns around data sovereignty, cost predictability, and seamless integration.

One striking detail: customers can even rent "half a cluster" or "half a rack," offering granular modularity few cloud providers match.

Why Neoclouds Like GMI Are Winning

1. Cost Efficiency

Traditional CSPs charge premiums and rely on customer lock-in. Neoclouds like GMI deliver high performance without the bloat or lock-in tax.

2. Personalized Support

Unlike hyperscalers where premium support is reserved for million-dollar contracts, GMI Cloud provides direct Slack access to the engineering team and even to Alex himself.

"If you have a problem, you can reach the CEO."

3. Low-Latency, Global Infrastructure

GMI Cloud operates data centers in Singapore, Taipei, Thailand, and the U.S. with Japan launching soon, enabling real-time AI services across APAC and North America.

4. Deep NVIDIA Ecosystem Focus

Rather than splitting engineering resources across multiple GPU ecosystems, GMI Cloud focuses exclusively on NVIDIA, maximizing CUDA optimizations and AI framework compatibility.

The Inference Boom: The Real AI Scaling Challenge

A major shift discussed was the move from AI training to AI inference.

Since the release of high-performing models like DeepSeek, inference workloads now account for over 55% of new customer activity at GMI Cloud.

"Training is no longer the bottleneck; serving AI models efficiently and globally is the new frontier."

As real-time AI assistants, agents, and content generators explode, speed, latency, and cost dominate infrastructure needs.

This isn’t a slowdown; it’s an acceleration.

Beyond the Cloud: The Coming Wave of Physical AI

Alex also shared a powerful vision: Physical AI, robots trained with real-world interactions captured via teleoperation.

Imagine:
🤖 Workers in Asia operating robots in the U.S. via VR gloves
🤖 Real-world data streaming to train next-gen robotics models
🤖 Manufacturing reshored to the U.S., powered not by cheap labor, but by highly skilled teleoperators and AI models

"In three to five years, we'll see real-time teleoperated robots gathering data at scale," Alex predicted.
"Physical AI is coming much faster than most people expect."

And behind these robots?
Cloud infrastructures that are modular, AI-native, and globally distributed, exactly like what Neoclouds are building today.

Conclusion: Modular, Borderless, AI-Native

The cloud is evolving.

As AI reshapes how applications are built and served, companies need clouds that are:

  • Modular

  • AI-optimized

  • Globally distributed

  • Relentlessly customer-centric

Neoclouds represent this future.

And GMI Cloud, with its Shopify-for-AI vision and deep modularity, is at the forefront.

"The winners of the AI era," Harry concluded, "won't be those clinging to yesterday's clouds; they will be those building tomorrow's."

The future is modular.
The future is Neocloud.

🎧 Listen to the full podcast episode:
EP85|AI時代的雲端新勢力:What Are Neoclouds? An Interview with GMI Cloud Founder & CEO Alex Yeh

🚀 Want to experience the next generation of cloud infrastructure?
Discover how GMI Cloud’s AI-native platform can power your AI innovation — with modular solutions, global reach, and unmatched flexibility.

👉 Learn more about GMI Cloud here.

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