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Chips of the Trade: TSMC, Samsung Benefit from AI Demand

In international markets, a big theme of investor interest relates to companies developing the underlying technology that powers AI. This includes the designers and manufacturers of the advanced semiconductors necessary to run AI, as well as producers of semiconductor manufacturing equipment and providers of the critical computing infrastructure required by AI systems.

Expectations are that semiconductor industry revenue growth will accelerate to annualized double-digit levels this decade, spurred by demand for AI chips. This would be a growth rate well above levels that we’ve seen since the mid-1990s, with predictions that the roughly US$50 billion dollars of AI chips sold in 2023 could rise to US$400 billion dollars of sales before the end of the decade.

While US chip designer NVIDIA gets most of the AI press, TSMC manufactures virtually all of the high-performance AI chips designed by NVIDIA. The Taiwan-based company uses some of its most sophisticated manufacturing technologies for these chips, enabling them to be at the forefront of transistor density, speed, and energy efficiency. AI chip customers also increasingly depend on TSMC’s innovative capabilities in integrating and packaging the logic, memory, and input/output components involved. TSMC’s CEO recently projected that in four years about 20% of this company’s total revenue would come from AI-specific chips.

Samsung Electronics has received less attention from investors but is also carving out a niche for itself in AI-related semiconductor manufacturing. Samsung anticipates a rebound in their memory chip prices in 2024, in part due to the expected proliferation of on-device AI, a memory-hungry implementation, and is investing for longer term in the next generation of high-bandwidth memory chips integral to AI applications, promising to leapfrog competitors in performance. Samsung Electronics is also positioning itself to compete with TSMC in manufacturing advanced logic chips, using its capability of designing and manufacturing memory, logic, and chip packaging to unlock new opportunities for its foundry business.

Infineon, widely recognized for its strength in automotive and power semiconductors, is less directly exposed to AI themes but does have products supporting growth data centers and AI computing whose high-power demands is a good match for Infineon’s switched mode power supplies and voltage regulator designs that power high performance systems.

Image source: Synopsys as of 2024. 1Global Semiconductor Sales – Sources: SIA/WSTS (historicals); forecasts based on Gartner, TechInsights, IBS, SIA/WSTS and consensus analyst forecasts for leading semiconductor companies. 2Explosion in Demand for AI Chips – Sources: Gartner, AMD, NVIDIA, Intel, Goldman Sachs.

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NVIDIA and the Cautionary Tale of Cisco Systems

NVIDIA, the giant semiconductor company founded by Taiwanese American Jensen Huang, seems invincible these days. Annual revenue has more than doubled since 2020. Its stock price has more than doubled this year and is up more than 700% over the past five years. It is one of the rare trillion-dollar market-cap companies.

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Meta Accelerates Its AI Game

Meta has been quieter about its artificial-intelligence-focused endeavors this year than some of its big-tech peers like Microsoft and NVIDIA, but it expects just as massive a transformation of its business from the much-hyped technology.

In its second-quarter earnings conference call, Meta founder and CEO Mark Zuckerberg detailed how AI permeates the company. For example, nearly all of Meta’s advertisers now use at least one AI-based product, allowing them, for instance, to personalize and customize ads. He also touted an increase of 7% in time spent on Facebook after launching AI-recommended content from accounts that users don’t follow.

Now the company plans an aggressive push of its own version of generative AI, the kinds of large language models that have gotten so much attention lately. In July, the company released an open-source—i.e., free for even commercial use—generative AI platform called Llama 2, which Meta hopes will emerge as a competitor to OpenAI’s GPT-4. Meta is betting its platform will unleash users’ creative potential and result in a flood of content. If that occurs, Meta’s powerful algorithms for matching content with users—4 billion of them across all of its platforms—will become indispensable as a content-discovery tool with a rich set of monetization options from advertising to ecommerce to subscriptions.

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Generative AI Through a Fundamental-Research Lens

The following is an excerpt from our second-quarter report for the Global Equity strategy. Click here to read the full report.

Anyone who has interacted with popular AI models—asked them about the mysteries of life and the cosmos or created convincing Van Gogh replicas using AI-enabled image generators—can sense that we may be in the midst of a technological revolution. That prospect has consumed equity markets lately, with seven US tech-related stocks responsible for most of the market appreciation in the second quarter.

As an investor in high-quality, growing businesses, we have always tried to position this portfolio to benefit from secular trends, the kind that transcend economic cycles and are driven by fundamental changes in key areas such as tech. Still, it is incredibly difficult for anyone to predict how such trends will unfold; the vicissitudes of cryptocurrency are a sobering reminder of this. Furthermore, as seen with the rise of the internet and, later, mobile connectivity, technology is merely a platform; it’s the applications of the technology that eventually determine many of the winners and losers. In the case of generative AI, some of the future applications may not yet be conceivable, although many companies, even outside the tech field, are now pondering the possibilities.