checkmate

When investors think about powerhouses in the semiconductor industry, the usual names that dominate the conversation are Nvidia, Advanced Micro Devices, and Broadcom. These companies are responsible for designing the high-performance chips and networking hardware powering next-generation data centers at an unprecedented scale.

Operating more quietly in the background, however, is Taiwan Semiconductor Manufacturing (TSM -1.17%). While TSMC (as it is also known) is less flashy than its peers in the race for artificial intelligence (AI) chips, the company’s supporting role is nonetheless mission-critical.

As the world’s largest chip foundry by revenue — with almost 70% market share — TSMC is the manufacturer behind many of the AI industry’s most advanced processors. Its dominance has left rivals like Intel struggling to catch up, with meaningful market share gains appearing more like a pipe dream than measurable reality.

But in a surprising twist, Tesla CEO Elon Musk recently highlighted a big break for one of those rivals, Samsung Electronics (SSNL.F 9.01%), giving its investors some much-needed optimism. The announcement raises an important question: Will Samsung’s latest win usher in a new era of growth and pose a serious challenge to TSMC’s supremacy?

Why Samsung’s deal with Tesla matters

In late July, Musk announced on X that Tesla had signed a $16.5 billion agreement with Samsung to produce its next-generation inference chip, known as the AI6. Samsung will be manufacturing these chips at a new foundry in Texas, strategically positioning the company closer to Tesla’s headquarters and reinforcing its footprint beyond South Korea.

Tesla’s upcoming innovations — most notably its Robotaxi platform and Optimus humanoid robot — will demand highly sophisticated chip designs and huge computing capacity to function. This makes securing advanced foundry services essential for the company’s ambitions in a rapidly evolving AI landscape.

Image source: Getty Images.

How does Samsung’s relationship with Tesla impact TSMC?

At first glance, a deal of this magnitude might look like a major setback for TSMC. The reality, however, is more nuanced.

Musk clarified that TSMC will manufacture the predecessor chip to the AI6 — aptly called the AI5. In other words, Tesla is deliberately engaging with multiple foundry partners as a strategic, cautious hedge aimed at reducing supply chain risk and ensuring redundancy.

While Samsung’s win provides a boost of credibility to its lagging foundry business, analysts at Morgan Stanley said that the deal is unlikely to meaningfully dent TSMC’s dominance or serve as a material headwind to its long-term revenue and earnings potential.

Moreover, as TSMC continues to invest in its own infrastructure here in the U.S., the company remains on secure footing to deepen its ties with AI’s biggest spenders even further.

Has Samsung delivered a checkmate against its fiercest rival?

Samsung investors have gained tangible proof that strengthens the company’s long-term prospects, but TSMC’s durable technological position remains supported by entrenched scale, advanced processor leadership, and deep customer relationships. For now, this deal underscores that Samsung can still compete for landmark contracts and carve out relevance in an industry where TSMC’s gold-standard reputation remains firmly intact.

At a more macro level, the deal also signals that as AI applications become increasingly more sophisticated, leading enterprises like Tesla are keen on maintaining choice by diversifying key manufacturing partners to ensure stability, flexibility, and supply chain resilience.

For investors, the larger takeaway is clear: Samsung’s relationship with Tesla illustrates that the company is capable of winning meaningful battles. Nevertheless, TSMC is still ahead.

Rather than a checkmate, this development looks more like a fleeting stalemate at best — a dynamic that will continue to evolve as global demand for next-generation chip architectures accelerates and further intensifies the foundry race.

Ever since OpenAI introduced ChatGPT to the public a few years ago, some Wall Street analysts have sounded the alarm for Alphabet (GOOGL -1.02%) (GOOG -0.96%). The concern is straightforward: As consumers increasingly turn to chatbots to answer queries, Alphabet’s long-standing dominance in Google Search could face disruption.

Since the bulk of the company’s revenue comes from advertising fees tied to search, any erosion in Google’s market share seemingly poses an existential threat to Alphabet’s financial engine. On the surface, this bearish narrative is compelling. But the reality is far more nuanced.

Alphabet’s financial resilience, strategic partnerships, and product evolution suggests that the company is not only prepared to defend its turf but may also emerge stronger in the face of rising competition.

Analyzing Alphabet’s financial fortress

In the table below, I’ve summarized Alphabet’s advertising revenue from Google Search over the past year:

Data source: Alphabet. YOY = year over year.

Given the profile above, there is little evidence that ChatGPT or other large language models (LLMs) represent material headwinds for Google’s dominance across the internet. The figures above suggest that advertisers continue to view Google as one of the most effective channels for capturing engagement and attention online.

What’s even more critical to recognize is that Alphabet’s advertising business operates at exceptionally high profit margins. This profitability provides the company with a powerful buffer. What I mean by that is if LLMs eventually chip away at Google’s market share, Alphabet is still well-positioned to absorb the impact by reinvesting this cash flow into next-generation products — a strategy the company is already executing today.

In recent years, Alphabet has poured significant resources into expanding its cloud infrastructure platform to better compete with Microsoft Azure and Amazon Web Services (AWS). At the heart of Google Cloud Platform (GCP) is its custom-built hardware, Tensor Processing Units (TPUs). These are specialized chips designed to handle advanced artificial intelligence (AI) workloads such as machine learning and deep learning.

In a striking development, OpenAI signed on as a major GCP client. The irony here is hard to dismiss: Even if ChatGPT diverts some internet traffic that might otherwise flow to Google, Alphabet still benefits financially on the back end by powering the very company allegedly threatening its leadership position.

Image source: Getty Images.

Turning Google into an LLM

Alphabet’s defensive posture extends well beyond monetization. The company has also integrated its own AI model, Gemini, across its ecosystem.

Within Google Search, users can now toggle into “AI Mode” — effectively transforming the search experience into an LLM-powered interface. By embedding a ChatGPT-like experience natively into Google, the company layers its own generative AI capabilities into the familiar query box.

This approach delivers two major advantages. First, it preserves ingrained user habits — making switching to other platforms less appealing. Second, it allows Alphabet to maintain robust advertising economics — albeit in a reimagined format.

Together, these moves underscore a dual positioning: defending the core search business while simultaneously profiting from the very companies seeking disruption. Put differently, Alphabet isn’t treating LLMs as a binary threat. Instead, the company has created a hedge that few can match — making money whether users type a query into Google or send a prompt to ChatGPT.

Is now a good time to buy Alphabet stock?

While OpenAI currently commands much of the cultural and technological AI spotlight, Alphabet’s response is more than simple defensive insulation. The company is actively reshaping its narrative — repositioning itself as a business woven together by AI-powered services.

GOOGL PE Ratio (Forward) data by YCharts

The valuation expansion outlined above suggests that investors are now just beginning to recognize the breadth of Alphabet’s AI story. Yet, based on forward earnings, the market has not assigned the same premium to Alphabet as other beneficiaries of the AI revolution.

Alphabet may not have declared a “checkmate” against OpenAI, but it has clearly moved past a stalemate. With its shares trading at a steep discount to its peers, I see Alphabet stock as a compelling opportunity as the company’s AI investments continue to bear fruit.

Few figures in the business world command attention quite like Elon Musk. Known for his ability to shape narratives and capture Wall Street’s attention, he has once again grabbed the spotlight — this time with comments about Tesla‘s (TSLA 2.27%) ambitions to design its own artificial intelligence (AI) chips.

Just had a great design review today with the Tesla AI5 chip design team! This is going to be an epic chip.

And AI6 to follow has a shot at being the best by AI chip by far.

Switching from doing 2 chip architectures to 1 means all our silicon talent is focused on making 1…

— Elon Musk (@elonmusk) September 6, 2025

Tesla’s efforts to move into custom silicon could be significant for the company’s next-generation products — but what might they mean for semiconductor powerhouse Nvidia?

What is the AI5 chip, and why does it matter?

AI5 — and its successor AI6 — are simply Tesla’s internal codenames for its next generation of custom chips. While Musk’s comments may fuel a debate over which company is designing the most advanced silicon, investors should look past the surface-level narrative. His underlying message points to something larger: Tesla is pursuing deeper vertical integration of its technology stack.

The rationale is straightforward. By consolidating its high-end computing onto a single family of purpose-built chips, Tesla gains greater control over both performance and cost — and can streamline engineering cycles and accelerate product development. From a financial perspective, this strategy also has the potential to improve unit economics by reducing supply chain risk and expanding profit margins over time.

Image source: Getty Images.

How do these investments impact Tesla’s AI ambitions?

Tesla’s AI ambitions can be divided into two categories: self-driving cars and humanoid robotics. While these markets target different end users, the unifying theme is autonomy.

Importantly, autonomy will not be achieved as a singular breakthrough — it will be the product of constant iteration. Both Tesla’s robotaxis and its Optimus robots rely on taking in fresh real-world data and using machine learning loops to steadily become “smarter” and more capable over time.

Is this a checkmate move against Nvidia?

Given the context above, it’s critical to note that Nvidia remains the leader in powering the training side of AI workloads. Tesla may have bold ambitions in custom silicon design, but the key question for investors is whether its efforts could truly disrupt Nvidia’s dominance in the data center landscape.

At present, I see that as highly unlikely. Nvidia’s entrenched position — anchored not only by its hardware but also by its widely used CUDA computing platform — gives the company broad ecosystem advantages. Coupled with its rapid pace of product development — it rolled out its Blackwell Ultra GPUs earlier in this quarter, and will launch its next-gen Rubin GPUs in 2026 — these factors make it difficult for any competitor to materially erode Nvidia’s lead in AI infrastructure at this time.

Nvidia’s dominance is not solely a function of its chips. Rather, the company’s comprehensive hardware-software stack creates immense friction for enterprises considering moving some of their business to rival platforms. This creates a formidable technological moat and durable competitive advantage for Nvidia.

With this in mind, the broader takeaway is that Nvidia’s flywheel is unlikely to come to a sudden halt simply because one company is choosing to become more self-reliant. While Tesla may eventually compete with Nvidia in the autonomous vehicle chip market, it is quite likely to remain a complementary player — or even an Nvidia customer — when it comes to AI training protocols.

Against this backdrop, Tesla’s progress in developing its own infrastructure is notable, but those efforts are still in their early stages. All the while, Nvidia continues to roll out improved successor architectures to its already industry-leading GPUs.

The bottom line is that while Tesla may find ways to meet some of its chip needs in-house over time, it is still far from achieving a checkmate position against the AI chip leader.