AI and The NVIDIAs AI Revolution – Why This Story Is Much Bigger Than a Chip Company.
- Noel Ong
- Apr 27
- 13 min read
I started to look at the world of Artificial Intelligence (AI) seriously 12 months ago with a trip to the SuperAI Conference in Singapore in 2025. This event was so impactful that I will be attending again this year on the 10th and 11th June 2026. As part of the AI revolution for the Samso Platform, I sought out practitioners of the industry to join me for a Coffee with Samso. My goal was to get an "AI for Dummies" approach to kickstart our journey into AI. I found Eric Starling, who provided a solid introduction to the world of AI. It's not that the general public lacks understanding of AI and its implications; rather, I wanted insight into how industry players perceive the world of AI.
Check out the Coffee with Samso with Eric Starling:
What I learned from Eric Starling, who was then the Principal Innovation Advisor at Amazon Web Services (AWS), was that AI is essentially coding, now referred to as English. The concept is simple: programming has advanced significantly over the last decade, aided by technological improvements in hardware and the proliferation of data centres. This evolution has enabled the resolution of various software issues.
Understanding AI from an Investor's Perspective
As an investor, I wanted to delve deeper into the mechanisms, components, and levels of AI's workings. I am particularly interested in what is currently fueling the excitement among AI stakeholders.
There are moments in markets when investors become so focused on price charts, quarterly earnings, and the latest headlines that they overlook the deeper structural changes taking place. The current excitement surrounding artificial intelligence feels like one of those moments. Many people look at NVIDIA and see a company whose share price has surged due to its production of chips essential for AI systems. While this observation is accurate, it is also incomplete.
The Insights of Jensen Huang
To truly understand what is happening, investors must step back from the noise and listen closely to Jensen Huang, the CEO of NVIDIA. Huang does not speak like a typical executive trying to sell a product cycle. Instead, he describes a transformation in industrial architecture. His language consistently revolves around platforms, factories, infrastructure, ecosystems, and the future shape of productivity. This message is vastly different from merely selling faster semiconductors.
I watched Jensen Huang speak at the PMWC 2025 (Precision Medicine World Conference) and thought he was spot on. While it appeared to be a speech at a healthcare and precision medicine conference, it was about AI transcending the technology sector and integrating into the operational frameworks of real industries.
Jensen Huang is a well-known figure in the semiconductor world, but it is essential to remember that other semiconductor giants also exist. Companies like TSMC, Broadcom, AMD, Samsung, and Intel dominate key areas such as foundry services, logic chip design, and memory. While NVIDIA is the leading fabless designer, TSMC is the world's largest manufacturer (foundry) of advanced AI chips. Companies like ASML are critical for providing the lithography machines necessary for production.
Here is a good summary of the list of semiconductor players that matter:
Readers and investors must realize that the world of data centres and the energy required to power our children's and grandchildren's futures will differ significantly from our current world and that of our great-grandparents.
The Market Sees Chips. NVIDIA Sees Infrastructure.
The simplest way to understand NVIDIA is to say it designs GPUs. This explanation may have sufficed years ago when graphics processors were mainly associated with gaming and visual computing. Today, however, this definition is outdated and no longer represents the true source of value.
What NVIDIA increasingly provides is infrastructure for machine intelligence. The chips are just one part of the stack. Surrounding them are software, networking, developer tools, data centre architecture, robotics frameworks, digital twin environments, and a developer ecosystem that has taken years to build.
This complexity is why many of NVIDIA's competitors find the story harder than expected. Designing a chip is challenging, but replicating an ecosystem is even more difficult. Investors often underestimate this distinction because financial markets prefer neat classifications. They want to categorize companies into sectors. Yet some companies evolve beyond their original categories.
The efficiency of AI hinges on the database from which the AI is trained, and this is a crucial aspect that investors often overlook. Companies like Echo IQ Limited (ASX: EIQ) can have an "AI Agent" that makes a difference because they train their AI using an exclusive dataset that is unparalleled in their field of influence. Achieving milestones validated by rising market capitalisation is the ultimate recognition of success.
Check out the latest Coffee with Samso with Echo IQ Limited:
In this context, NVIDIA has transformed from a semiconductor company into an enablement company. It assists others in building the future more rapidly. The recent partnership with Nokia clearly illustrates NVIDIA's vision. By adding value to its business chain, NVIDIA is redefining its role.
The NVIDIA AI Revolution - Why Semiconductors Have Become Strategic Assets
For many years, semiconductors were viewed as crucial but largely invisible components of the global economy. Consumers cared about phones, laptops, gaming consoles, and internet services, but few considered the chips inside them.
Today, advanced semiconductors influence military systems, cloud computing, scientific modelling, industrial automation, language models, robotics, and national competitiveness. The chip sector is no longer a quiet supplier in the background; it has become a frontline player in economic power. On equity exchanges such as the ASX, the mere mention of "semiconductor" can impact price and company valuation, rendering the term itself a significant factor.
The extent of its importance has led governments to discuss semiconductors in strategic terms. One might even think that wars could be sparked by who controls semiconductor production, similar to oil and minerals.
Export controls, domestic manufacturing subsidies, supply chain resilience, and sovereign capability are now common policy themes. The world has recognized that computational power is not just a commercial advantage; it is a geopolitical asset.
When markets grasp this shift, valuations across the semiconductor ecosystem begin to make more sense. This is no longer merely about cyclical demand for consumer electronics; it is about controlling the digital production layer of the next economy. It is about how the NVIDIAs of the global semiconductor sector manage their business infrastructure and influence the way humanity will function as we transition into a new era of coexistence with machines.
AI and The NVIDIAs - Why Healthcare Was Such an Important Signal
When Huang spoke at PMWC, it was evident that he foresaw the significance of the healthcare setting. Healthcare is not known for adopting change quickly; it is regulated, complex, data-heavy, and rightly cautious. If artificial intelligence can gain traction in such an environment, it suggests that the technology has moved beyond novelty.
Medicine generates vast amounts of information. Imaging scans, pathology results, genetic data, patient histories, treatment responses, and administrative workflows all create layers of complexity that traditional systems struggle to process efficiently. AI is well-suited for environments where patterns are hidden within large datasets.
This means the real opportunity may not be a robot replacing doctors, as some headlines imply. Instead, it may involve systems that improve diagnosis speed, identify risks earlier, streamline workflows, support clinical judgement, and reduce waste.
From a Samso perspective, this is where investors should focus. The best technologies often do not create the loudest headlines; they are the ones that quietly solve expensive problems.
What This Means for the Wider Semiconductor World
For investors and the global community, the need for NVIDIAs to succeed is just the beginning. The demand for data infrastructure and the energy required to support this exponentially growing industry is just the tip of the iceberg. This is a thought that should not be underestimated.
A large AI buildout pulls demand through multiple layers of industry. Chip designers need foundries. Foundries require equipment. Servers need memory. Data centres need cooling, electricity, land, and network connectivity. Software companies need complete access. Enterprises require consultants and integration partners.
The fear of humans being replaced by machines is exaggerated. The relationship between machines and humans is more interconnected than the narratives circulating in the media suggest.
This is why significant structural themes rarely reward only one company. Railways created demand for steel, coal, engineering, land development, and finance. The internet generated opportunities in hardware, software, logistics, media, payments, and advertising. AI is likely to do the same.
This broader perspective is important because investors often arrive late to headline names and overlook the surrounding ecosystem where value may still be emerging.
NVIDIA and Nokia: The Marriage that will Drive The Future Digital Infrastructure Story
This partnership should serve as a wake-up call for investors examining this sector. What we once labeled as the AI sector can no longer be categorized in that manner. If I were to put on my thinking "hat," this sector is evolving into something beyond just AI and software.
The AI narrative is no longer solely about better software. It is transforming into a story about power, chips, networks, data centres, fibre, edge computing, and the capacity to move intelligence closer to decision-making.
This is what the NVIDIA and Nokia combination could set as a trend for the future of communications. NVIDIA is constructing the compute layer of the AI world. Its Blackwell architecture is designed for large-scale generative AI and accelerated computing, featuring GPUs, CPUs, and networking built as a full-stack data-centre platform.
Nokia, on the other hand, is focused on the connectivity layer. Its AI-RAN strategy aims to integrate artificial intelligence into the radio access network, ensuring that future 5G-Advanced and 6G networks are not merely communication pipes but intelligent infrastructure. Nokia describes AI-RAN as three components: AI improving the network, AI operating on the network, and AI sharing infrastructure with the network.
“It’s driven by two exponentials,” [two growth curves happening simultaneously.] Huang stated. “We now have visibility. I think we’re probably the first technology company in history to have visibility into half a trillion dollars of cumulative Blackwell and early ramps of Rubin through 2026. As you know, 2025 is not over yet, and 2026 hasn’t started. This is how much business is on the books. Half a trillion dollars worth, so far. We’ve already shipped 6 million of the Blackwells in the first several quarters. . . . We still have one more quarter to go for 2025 and then we have four quarters [referring to 2026]. So the next five quarters, there’s $500 billion, half a trillion dollars. That’s five times the growth rate of Hopper [NVIDIA Hopper was already one of the fastest-selling enterprise compute platforms in history.].”
Or, put simply:
Demand for AI is exploding, and the computing needed for each AI system is also exploding. Those two forces together are creating unprecedented order momentum for NVIDIA.
The key takeaway is this: AI will not transform the world by remaining confined within a data centre. It needs to travel. It requires reduced latency. It demands edge processing. It requires network reliability. It needs energy-efficient infrastructure. This is why NVIDIA’s US$1 billion investment in Nokia in October 2025 is significant. This partnership aims to accelerate AI-RAN innovation and facilitate the transition from 5G to 6G.
For investors, this represents a crucial shift in perspective. The AI opportunity extends beyond models and applications; it also encompasses the essential backbone: data centres, optical networks, telecom equipment, high-performance chips, cooling, power, and software-defined networks.
Nokia’s recent comments underscore this point. Its CEO cautioned that Europe risks falling behind the US and China if it does not develop sufficient AI data-centre and connectivity infrastructure. This indicates that AI is now regarded as national infrastructure, not merely a technology sector.
The NVIDIA–Nokia relationship also hints at a future where telecom networks become integral to the AI economy. Nokia and Orange are already collaborating with NVIDIA on AI-RAN use cases that may enhance spectral efficiency, radio performance, and new services like integrated sensing and communication.
My Samso view is straightforward. The next phase of AI will be dominated by those who control both intelligence and delivery. NVIDIA provides the AI world with processing power. Nokia aims to make the network intelligent enough to carry that power into the physical world.
This is why digital infrastructure is crucial. Without it, AI remains powerful but centralized. With it, AI becomes distributed, responsive, and embedded into everyday systems — factories, hospitals, vehicles, cities, mining operations, logistics, defence, and communications.
The future AI landscape may not be defined solely by who has the best model. It may be shaped by who possesses the best infrastructure to make AI practical in the real world.
The Australian Perspective
It is unlikely that Australia will host the leading global GPU designer. However, this does not mean Australia is excluded from the narrative. Some companies may emerge, but the race will be dominated by the giants mentioned earlier.
Australia can, however, play a significant role in components that are part of the future AI-driven pathway. Plans are underway to construct the nation’s largest data centre in the remote northern area of Western Australia to support large-scale artificial intelligence (AI) training, including platforms like ChatGPT (ABC News).
Project Meridien, powered by wind, solar, and natural gas, is expected to provide approximately 240 megawatts of IT capacity and involve an investment of billions of dollars. This "AI factory" is planned to be developed in stages on Karajarri land, located south of Broome in the Kimberley, approximately 2,000 kilometers north of Perth, with an expected opening in 2032.
Gingerah Energy, the joint venture leading the project, is spearheaded by chief executive Jop van Hattum. He mentioned that the project would expand on the initial 240 megawatts of IT capacity.
"Ultimately, the project will be four times larger," he stated.
"The chosen site allows for a 1 gigawatt IT facility."
Every major technology cycle requires raw materials, energy, infrastructure, and specialist applications. Australia has relevance in each of these areas. Copper, rare earths, nickel, uranium, and high-quality iron ore all intersect with industrial modernization in various ways. Reliable energy becomes increasingly important as data centres consume more power.
Beyond resources, Australia may also produce niche software and healthcare technology businesses that apply AI to specific problems rather than attempting to build global foundational models. In many cases, this can be the more practical commercial path.
Samso readers should remember that not every winning investment must be the inventor of the platform. Sometimes, it is enough to own a business that benefits from the platform becoming essential.
The Risk of Believing Every AI Story - A Reality Check For Investors
No significant investment theme arrives without exaggeration. Markets are inherently enthusiastic, and promoters quickly learn to attach themselves to fashionable narratives.
This means investors need discipline. Not every company mentioning AI has a defensible product. Not every high valuation reflects durable earnings power. Not every pilot program evolves into a real business.
The challenge lies in distinguishing genuine utility from borrowed excitement. This requires asking grounded questions. Does the technology address a genuine pain point? Will customers pay for it? Can it be deployed at scale? Is the competitive advantage real? Can management execute?
These questions matter more than whether the presentation deck uses the letters A and I fifty times.
The Samso View
Jensen Huang’s significance may ultimately have less to do with one company’s market capitalisation and more to do with how clearly he has articulated the next phase of computing. He has consistently framed AI as infrastructure, not entertainment. As productivity, not novelty. As industrial capacity, not a fleeting software trend.
This framing is worth understanding. Markets will overshoot at times. Valuations will fluctuate. Competitors will emerge. Cycles will come and go. But structural shifts tend to endure despite the surrounding volatility.
The current AI era may be remembered less as the rise of chatbots and more as the moment intelligence became embedded into the operating systems of industry. That is a much larger narrative than one chip company.
Samso Final Thoughts
Investors often ask whether they have missed NVIDIA. That may be the wrong question. A better question is whether they understand what NVIDIA represents.
If AI becomes foundational infrastructure, opportunities will continue to arise across semiconductors, power, resources, software, healthcare, logistics, and automation. The winners may not always be obvious in the early stages.
The real edge comes from recognizing the second-order effects before the crowd does. That is usually where thoughtful investing begins.
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