Bull of the Day: Taiwan Semi (TSM) | TSMC Revenue Climbs 39% in Latest Sign of AI Spending Boom |…

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Bull of the Day: Taiwan Semi (TSM)

Taiwan Semiconductor (TSM) is the premier chip fabrication company for the world's most advanced digital technologies, from Apple smartphones to NVIDIA GPUs.In less than five years, TSMC's trailing 12-month revenue has more than doubled to hit $95 billion as of the March quarter. Clearly, this is on the back of NVIDIA's (NVDA) explosive growth which saw sales grow by ten times in the same period to $148.5 billion as of the April quarter, on its way to nearly $200 billion this fiscal year (ends January).Of course, demand for NVIDIA GPU systems didn't turn into a hockey stick until its "ChatGPT moment" in the spring of 2023.I mark that moment in late May at Computex in Taipei City, Taiwan when Jensen Huang unveiled the DGX Grace Hopper 200 system and said that Microsoft, Google, and Meta Platforms (META) were already in line.To me, this meant that the other 996 corporations in the Fortune 1,000 would want (or need) to build their own LLMs too. I then published this article and video to explain what was coming…Nvidia DGX: Workhorse of AI Will Drive NVDA to $2 TrillionAnd that $2 trillion market cap came quickly. That's when the "AI bubble" talk started. You can imagine how astonished the bubble breathers are now that NVDA is approaching a $4 trillion market cap."Honey, I Shrunk the Chips!"While Apple's business has been significant for TSMC (as much as 25% of revenues), the iPhone maker's sales growth has stalled in the low single digits.What still makes Apple very important though is how they help drive innovation at TSMC by always demanding the latest and greatest architectures for their ecosystem of devices.TSMC supplies chips for flagship smartphones and 5G infrastructure, where efficiency and miniaturization are crucial. The company’s 5nm and 3nm transistor nodes are widely adopted in high-end mobile devices and 5G equipment, supporting the global rollout of next-generation connectivity.Transistor nodes refer to the specific manufacturing processes used to produce integrated circuits, where the "nm" (nanometer = 1 billionth of a meter) like 7nm or 5nm, historically represented a physical dimension of the transistor, specifically the gate length. For reference, the coronavirus is about 50nm.Now it's more of a marketing term that signifies a new generation of chip technology with improved performance, power efficiency, and transistor density.But generally, a smaller node number means…Smaller transistors: More transistors can be packed into the same area on a chip.Faster switching: Electrons have a shorter distance to travel, leading to higher clock speeds.Lower power consumption: Less voltage is needed to operate the smaller transistors.Why the AI Economy is Not a BubbleWhich brings us back to NVIDIA as they now pack 208 billion transistors into the Grace Blackwell "superchip" with further density on the horizon in the Rubin and Feynman series of GPUs expected in 2026 and 2027, following Jensen's nearly annual cadence of development.I mentioned the early demand for NVIDIA systems in 2023 and have recently seen similar projections from Goldman Sachs, Bank of America, and Marvell (MRVL) at their Custom AI Investor Event that total datacenter capex by the big "hyperscalers" (Amazon, Microsoft, Google, Oracle) plus Meta, Tesla (TSLA), OpenAI, Apple, and xAI, will grow from nearly $600 billion this year to over $1 trillion in 2028.This demand is not slowing down because all these companies realize that the transition to an "AI economy" is built on the infrastructure of NVIDIA GPU systems. I am on record late last year saying that this megatrend would lead to over $500 billion in revenues for NVIDIA by 2030. That's only ~35% CAGR from when the TTM topline crossed $100 billion.And that's the infrastructure to power not just generative and agentic AI systems (i.e., LLMs), but a whole new world of "physical AI" for autonomous machines, including self-driving cars, humanoid robots, and many other types of 3D automation requiring "embodied" or edge intelligence and vision/spatial perception.

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