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Semiconductors Paving Way for Generative AI Boom

Generative artificial intelligence (AI) is taking shape in significant fashion this year. With more AI growth avenues evolving, foundational elements are receiving more attention. Those include semiconductors, which are the picks and shovels of a variety of disruptive technologies.

That’s true of AI, and select semiconductor equities and exchange traded funds reflect investors’ expectation that AI-driven growth as it pertains to the chip industry is just getting started. Just look at the VanEck Semiconductor ETF (SMH A-). Home to one of the largest weights to Nvidia (NVDA) among all ETFs, SMH entered this week with a year-to-date gain of more than 51% while hovering around 52-week highs.

Interestingly, the recent history of select disruptive technologies, some which are semiconductor-dependent in their own rights, underscores the importance of chips in the AI industry. Last decade, machine-learning technology accelerated in earnest, supported by advancements in cloud computing and cost reductions on computers.

That’s been to the benefit of some SMH components. Still, the good news is that machine-learning advancements are more floor than ceiling when it comes to AI-related chip demand.

If history is an accurate guide, it’s possible that at some point during the AI/semiconductor journey, Wright’s Law will kick in. In simple terms, Wright’s Law attempts to forecast cost declines that correspond with production increases.

For semiconductor companies making AI inroads, the bulk of the wares they currently sell to end users are highly expensive. As production efficiencies are realized, costs can decline. However, chip companies may not be vulnerable to retreating profitability due to robust demand.

“Semiconductors for high performance computing are very large, and the amount of computing resources consumed rises exponentially with successive iterations of generative AI systems,” noted BNP Paribas. “This means microchips are getting larger with each generation, which drives wafer demand. In the long term, this should be positive semiconductor capital equipment and materials companies.”

Examples of semiconductor capital equipment companies include Asml Holding NV (ASML), Lam Research ((LRCX) and Applied Materials (AMAT). That trio combine for nearly 14% of the SMH portfolio.

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Some firms and other SMH holdings are establishing AI leadership roles, which could pay substantial dividends over the long haul.

“We continue to believe that the leaders and beneficiaries of digital transformation will deliver superior revenue growth, earnings, cash flows and returns over a long-term investment horizon,” concluded BNP Paribas.

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// UPDATED ON 21/09
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