Noah’s Black Diamond Summit. PHOTO: ARK WEALTH
As global financial landscapes shift, Noah outlines a new AI-first approach to helping families protect and grow their wealth.
Updated
December 11, 2025 11:33 PM
Noah’s Black Diamond Summit. PHOTO: ARK WEALTH
Noah Holdings, one of Asia’s leading wealth management firms serving global Chinese high-net-worth families, hosted its annual Black Diamond Summit in Macau from December 7–11. The city has become a significant gathering place for Noah’s community, where clients, partners, and experts converge each year to explore how global trends are transforming wealth and family life. This year’s theme, “AI Together, Co-Generating the Future”, set the tone for a conversation about how modern wealth management must adapt in an age defined by artificial intelligence.
More than 3,000 attendees joined discussions that connected technology, global mobility, and long-term family planning. The Summit built on earlier sessions held in Shanghai, creating a continuous dialogue around one central question: how can families prepare for a world that is becoming more digital, more complex and more interconnected?
A major moment came when Noah introduced “Noya”, its new AI Relationship Manager. Noya is now part of the upgraded iARK Hong Kong and Singapore apps. It is built to support licensed human advisors, not replace them. The goal is simple: combine human judgment with AI intelligence to help clients understand their wealth more clearly and manage it across borders. Noya offers real-time insights, deeper personalisation, cleaner access to global financial information, smoother coordination between regions, and end-to-end execution through Noah’s global booking centres.
The Summit’s tone shifted toward long-term thinking when Co-Founder and Chairwoman Norah Wang delivered her keynote, “From Chaos to Clarity: Building a Global Operating System for Wealth Management”. She reflected on twenty years of serving more than 400,000 clients and explained that families today face new pressures. As she put it, “The real pain point for Chinese families today is not investment performance, but navigating the growing complexities of a global lifestyle”. Her message was straightforward: wealth is no longer just about returns. It is about managing uncertainty in a world where technology, geopolitics, and mobility collide.
Wang described how two major shifts have shaped modern wealth—first the Internet Era, which changed how people built wealth, and now what she calls the AI Civilisation Era, which is changing how people must protect it. She outlined the forces that influence today’s decisions: geopolitical shifts, persistent inflation, the rising importance of security and supply-chain technologies, the spread of AI, and the need for stronger family governance across generations. Each of these factors adds complexity, and families need tools that help them see the bigger picture.
To respond to this reality, Noah presented its integrated global wealth infrastructure. It is built on three pillars:
Together, these pillars function as an AI-supported system designed to simplify global complexity and help families preserve long-term stability.
One of the most discussed conversations featured Noah’s CEO, Zander Yin, and Tony Shale, Co-Founder & Chairman of Asian Private Banker China. They spoke about how AI is transforming private banking in Asia. Their view was that wealth management is moving from a product-centred model to one led by insight, trust, and human-tech collaboration. AI may accelerate analysis, but human expertise will continue to guide judgment, relationships, and long-term strategy.
The closing message of the Summit centred on redefining what prosperity means in an AI-driven age. For Noah, wealth is no longer a destination. It is an ongoing journey through a world that is increasingly fast-moving and unpredictable. As Wang noted, “With AI reshaping the very foundations of civilisation, wealth and financial freedom represent not a static endpoint, but a continuous journey. Here, we find our purpose: to help global Chinese investors navigate an increasingly complex world and achieve true prosperity, supported by resilient wealth management infrastructure and deep human expertise”.
The Summit ended on that note—a reminder that the future of wealth is not only about financial assets, but about clarity, confidence and the ability to adapt as the world transforms.
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The hidden cost of scaling AI: infrastructure, energy, and the push for liquid cooling.
Updated
December 16, 2025 3:43 PM
The inside of a data centre, with rows of server racks. PHOTO: FREEPIK
As artificial intelligence models grow larger and more demanding, the quiet pressure point isn’t the algorithms themselves—it’s the AI infrastructure that has to run them. Training and deploying modern AI models now requires enormous amounts of computing power, which creates a different kind of challenge: heat, energy use and space inside data centers. This is the context in which Supermicro and NVIDIA’s collaboration on AI infrastructure begins to matter.
Supermicro designs and builds large-scale computing systems for data centers. It has now expanded its support for NVIDIA’s Blackwell generation of AI chips with new liquid-cooled server platforms built around the NVIDIA HGX B300. The announcement isn’t just about faster hardware. It reflects a broader effort to rethink how AI data center infrastructure is built as facilities strain under rising power and cooling demands.
At a basic level, the systems are designed to pack more AI chips into less space while using less energy to keep them running. Instead of relying mainly on air cooling—fans, chillers and large amounts of electricity, these liquid-cooled AI servers circulate liquid directly across critical components. That approach removes heat more efficiently, allowing servers to run denser AI workloads without overheating or wasting energy.
Why does that matter outside a data center? Because AI doesn’t scale in isolation. As models become more complex, the cost of running them rises quickly, not just in hardware budgets, but in electricity use, water consumption and physical footprint. Traditional air-cooling methods are increasingly becoming a bottleneck, limiting how far AI systems can grow before energy and infrastructure costs spiral.
This is where the Supermicro–NVIDIA partnership fits in. NVIDIA supplies the computing engines—the Blackwell-based GPUs designed to handle massive AI workloads. Supermicro focuses on how those chips are deployed in the real world: how many GPUs can fit in a rack, how they are cooled, how quickly systems can be assembled and how reliably they can operate at scale in modern data centers. Together, the goal is to make high-density AI computing more practical, not just more powerful.
The new liquid-cooled designs are aimed at hyperscale data centers and so-called AI factories—facilities built specifically to train and run large AI models continuously. By increasing GPU density per rack and removing most of the heat through liquid cooling, these systems aim to ease a growing tension in the AI boom: the need for more computers without an equally dramatic rise in energy waste.
Just as important is speed. Large organizations don’t want to spend months stitching together custom AI infrastructure. Supermicro’s approach packages compute, networking and cooling into pre-validated data center building blocks that can be deployed faster. In a world where AI capabilities are advancing rapidly, time to deployment can matter as much as raw performance.
Stepping back, this development says less about one product launch and more about a shift in priorities across the AI industry. The next phase of AI growth isn’t only about smarter models—it’s about whether the physical infrastructure powering AI can scale responsibly. Efficiency, power use and sustainability are becoming as critical as speed.