AI and The NVIDIAs AI Revolution – Why This Story Is Much Bigger Than a Chip Company.
- Noel Ong
- 14 minutes ago
- 14 min read
I started to look at the world in Artificial Intelligence (AI) seriously 12 months ago with a trip to the SuperAI Conference in Singapore in 2025, an event 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 hunted for practitioners of the industry to get on a Coffee with Samso to just give us the "AI for Dummies" approach to start our journey into AI. I found Eric Starling and he gave us a good introduction into the world of AI. It is not that we as the general public had no idea of what AI is and what it is doing, but what I wanted was an introduction to how the industry players view the world of AI.
Check out the Coffee with Samso with Eric Starling:
What I learnt from Eric Starling, who was then the Principal Innovation Advisor at Amazon Web Services (AWS), was that AI is simply coding which is now called English. The simplicity of the concept was that the world of programming with the help of technological advances in hardware and the generation of data centres, and with the help of the internet, exponentially advanced itself over the last decade to solve software issues.
As I am always trying to understand from the eyes of an investor, I wanted to explore the mechanism and the components and the levels of the workings of AI. I am also particularly interested in what is currently giving birth to the excitement of AI stakeholders.
There are moments in markets when investors become so focused on price charts, quarterly earnings, and the latest headline that they lose sight of the deeper structural change taking place underneath. The current excitement around artificial intelligence feels like one of those moments. Many people look at NVIDIA and see a company whose share price has risen sharply because it sells the chips needed to run AI systems. That observation is not wrong, but it is incomplete.
To understand what is happening, investors need to step back from the noise and listen carefully to what Jensen Huang, the NVIDIA man, has been saying over the past few years. Huang does not speak like a chief executive trying to sell a product cycle. He speaks like someone describing a change in industrial architecture. His language is consistently about platforms, factories, infrastructure, ecosystems, and the future shape of productivity. That is a very different message from simply selling faster semiconductors.
I watched Jensen Huang speak at the PMWC 2025 (Precision Medicine World Conference) and thought, this guy is again on the mark. On the surface, it was a speech at a healthcare and precision medicine conference but this was about AI moving beyond the technology sector and into the operating systems of real industries.
Jensen Huang is one of the most commonly watch "personality" in the semiconductor world but one has to remember that there are other semiconductor giants in the market as well. There are TSMC, Broadcom, AMD, Samsung, and Intel. These companies dominate key areas such as foundry services, logic chip design, and memory. While NVIDIA is the top fabless designer, TSMC is the world's largest manufacturer (foundry) of advanced AI chips, and companies like ASML are critical for providing the lithography machines required for production.
Here is a good summary of the list semiconductor players that matters:
Readers and investors need to realise that the world of data centres and the energy required to power our children's world and our great grandchildren's world is going to be so different to our current world and that of our great-grandparents.
The Market Sees Chips. NVIDIAs Sees Infrastructure.
The simplest way to understand NVIDIA is to say it designs GPUs. That may have been sufficient years ago when graphics processors were largely associated with gaming and visual computing. Today, as we all are fully aware, it is now much more and that explanation is no longer valid and is now no longer the real source of value.
What the NVIDIAs increasingly provides is infrastructure for machine intelligence. The chips are only one part of the stack. Around them sits software, networking, developer tools, data centre architecture, robotics frameworks, digital twin environments, and a developer ecosystem that has taken years to build.
This is why many competitors to NVIDIA find the story harder than expected. Designing a chip is difficult. Replicating an ecosystem is harder. Investors often underestimate this distinction because financial markets like neat labels. They want to classify companies into sectors. Yet some companies grow beyond the categories originally assigned to them.
The efficiency of AI is all about the database that the AI is training from and this is what investors miss. Companies such as Echo IQ Limited (ASX: EIQ) are able to have an "AI Agent" that is making a difference is because they are training their AI from an exclusive dataset that is second to none, in their field of influence.
To achieve the milestones that are currently being validated by a rising market capitalisation is the ultimate recognition of success.
Check out the latest Coffee with Samso with Echo IQ Limited:
In that sense, NVIDIA has evolved from a semiconductor company into an enablement company. It helps others build the future faster. The recent partnership with NoKIa is a clear vision of what NVIDIA is all about. What NVIDIA has done is to add value chain to its business.
The NVIDIAs AI Revolution - Why Semiconductors Have Become Strategic Assets
For many years, semiconductors were treated as important but largely invisible components of the global economy. Consumers cared about phones, laptops, gaming consoles, and internet services. Few thought deeply about 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 sitting in the background. It has become part of the front line of economic power. On equity exchanges such as the ASX, the mention of the word "semiconductor" moves price and company valuation, hence, the term semiconductor in itself is no longer "English".
The extend of its importance now have governments discussing semiconductors in strategic terms. One would think now that wars could be caused by who controls the production of semiconductors like oil and minerals.
Export controls, domestic manufacturing subsidies, supply chain resilience, and sovereign capability are now common policy themes. The world has realised that compute power is not just a commercial advantage. It is a geopolitical asset.
When markets understand this shift, valuations across the semiconductor ecosystem begin to make more sense. This is no longer simply about cyclical demand for consumer electronics. It is about control of the digital production layer of the next economy. It is about how the NVIDIAs of the global semiconductor sector manage their business infrastructure with their global influence of the way mankind will function as we move into a new way of living with machines.
AI and The NVIDIAs - Why Healthcare Was Such an Important Signal
When Huang spoke at PMWC, you can tell that he has already foreseen the importance and more importantly, that the healthcare setting mattered. 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 the technology has moved beyond novelty.
Medicine creates vast amounts of information. Imaging scans, pathology results, genetic data, patient histories, treatment responses, and administrative workflows all generate layers of complexity that traditional systems struggle to process efficiently. AI is well suited to environments where patterns are hidden inside large datasets.
That means the real opportunity may not be a robot replacing doctors, as some headlines imply. It may be systems that improve diagnosis speed, identify risk earlier, streamline workflows, support clinical judgement, and reduce waste.
From a Samso perspective, this is where investors should focus. The best technologies are often not the ones that create the loudest headlines. They are the ones that solve expensive problems quietly.
What This Means for the Wider Semiconductor World
For investors and in every aspect, the global community, the need for the NVIDIAs to succeed is just the beginning as the need for data infrastructure and hence the energy to drive this exponentially growing industry is just the tip of the iceberg. It is also a thought that should not be underestimated.
A large AI buildout pulls demand through multiple layers of industry. Chip designers need foundries. Foundries need equipment. Servers need memory. Data centres need cooling, electricity, land, and network connectivity. Software companies need complete access. Enterprises need consultants and integration partners.
The fear of humans being replaced as workers is not going to happen like the movies. The symbiotic relationship between machines and humans are more interconnected than the narrative that is circling the media airwaves at the moment.
This is why great structural themes rarely reward only one company. Railways created demand for steel, coal, engineering, land development, and finance. The internet created opportunities in hardware, software, logistics, media, payments, and advertising. AI is likely to do the same.
That broader lens matters because investors often arrive late to the headline name and ignore the surrounding ecosystem where value may still be emerging.
NVIDIA and Nokia: The Marriage that will Drive The Future Digital Infrastructure Story
This marriage should be the wake up call for investors looking at this sector. What we would have happily labeled as the AI sector cannot be tagged in that manner anymore. If I was to put on my thinking "hat", this sector is morphing itself to be more than just AI and software.
The AI story is no longer just about better software. It is becoming a story about power, chips, networks, data centres, fibre, edge computing and the ability to move intelligence closer to where decisions are made.
This what the whole NVIDIA and Nokia combination could be the trend setter for the future of communications. NVIDIA is building the compute layer of the AI world. Its Blackwell architecture is designed for large-scale generative AI and accelerated computing, with GPUs, CPUs and networking built as a full-stack data-centre platform.
Nokia, on the other hand, is working on the connectivity layer. Its AI-RAN strategy is about bringing artificial intelligence into the radio access network, so that future 5G-Advanced and 6G networks are not just communication pipes, but intelligent infrastructure. Nokia describes AI-RAN as three things: AI improving the network, AI running on the network, and AI sharing infrastructure with the network.
“It’s driven by two exponentials,” [two growth curves happening at the same time.] Huang said. “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 real point is this: AI will not transform the world by sitting inside a data centre alone. It needs to travel. It needs latency to fall. It needs edge processing. It needs network reliability. It needs energy-efficient infrastructure. This is why NVIDIA’s US$1 billion investment in Nokia in October 2025 matters. The partnership is aimed at accelerating AI-RAN innovation and helping the transition from 5G to 6G.
For investors, this is an important shift in thinking. The AI opportunity is not only in models and applications. It is also in the boring-but-critical backbone: data centres, optical networks, telecom equipment, high-performance chips, cooling, power and software-defined networks.
Nokia’s recent comments make this very clear. Its CEO warned that Europe risks falling behind the US and China if it does not build enough AI data-centre and connectivity infrastructure. That tells us that AI is now being treated as national infrastructure, not just a technology sector.
The NVIDIA–Nokia relationship also points to a future where telecom networks become part of the AI economy. Nokia and Orange are already working with NVIDIA on AI-RAN use cases that may improve spectral efficiency, radio performance and new services such as integrated sensing and communication.
My Samso view is simple. The next phase of AI will be won by those who control both intelligence and delivery. NVIDIA gives the AI world the processing power. Nokia is trying to make the network intelligent enough to carry that power into the physical world.
This is why digital infrastructure matters. Without it, AI remains powerful but centralised. 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 only by who has the best model. It may be defined by who has the best infrastructure to make AI useful in the real world.
The Australian Perspective
It's improbable that Australia will host the leading global GPU designer. However, this doesn't mean Australia is not part of the narrative. Some companies may but that race will be dominated by the giants we have mentioned earlier.
Australia can however play a role, and a significant role in componets that is part of the future AI hungry pathway. There are now ongoing plans to build the nation's largest data center in the remote northern area of Western Australia to support large-scale artificial intelligence (AI) training, including platforms such as 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 those areas. Copper, rare earths, nickel, uranium, and high-quality iron ore all intersect with industrial modernisation in different ways. Reliable energy also becomes more important when data centres consume increasing power.
Beyond resources, Australia may also produce niche software and healthcare technology businesses that apply AI to specific problems rather than trying 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 great investment theme arrives without exaggeration. Markets are enthusiastic by nature, and promoters quickly learn to attach themselves to fashionable narratives.
That 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 becomes a real business.
The challenge is to separate real utility from borrowed excitement.
That requires asking grounded questions. Does the technology solve a genuine pain point? Will customers pay for it? Can it be deployed at scale? Is the competitive advantage real? Can management execute?
Those questions matter more than whether the presentation deck uses the letters A and I fifty times.
The Samso View
Jensen Huang’s importance may ultimately have less to do with one company’s market capitalisation and more to do with how clearly he has explained the next phase of computing. He has consistently framed AI as infrastructure, not entertainment. As productivity, not novelty. As industrial capacity, not a passing software trend.
That 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 survive the volatility around them.
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 bigger story 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 appear 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 recognising the second-order effects before the crowd does.
That is usually where thoughtful investing begins.
The Samso Way – Seek the Research
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