Primitive versions of artificial intelligence (AI) have been around since the 1960s, but in recent decades advances in machine-learning algorithms, better access to big data, and enormous investments in computing power have made this tech lightning fast and eerily effective. And AI is advancing at a breakneck pace… with new stories about AI advances, ChatGPT, AI reading famously inscrutable ancient scrolls or building 3D models. Along with the technology comes the latest upheavals in the AI world, like the November 2023 ousting of Sam Altman, who was fired and rehired as CEO of OpenAI in a matter of days.
It harkens back to the advent of the Internet in the mid-1980s; it took some time to really take off over the next decades when computer scientist Tim Berners-Lee coined the “World Wide Web”. The number of websites grew from 130 in 1993 to over 100,000 by 1996. Today, everything related to the Internet has saturated the market; people are kind of looking for the next leg of growth and drivers for the future – artificial intelligence fits the bill.
AI was simply a hypothetical, a technology out of reach for most people, until generative AI, Microsoft AI, OpenAI and ChatGPT came to the surface. People/media are getting first-hand experience, asking ChatGPT to write an essay or ask for research. The more people that use it, the more they believe it. The AI app ChatGPT reached 100 million downloads in just two months, much faster than other popular apps such as TikTok and Uber.
The rapid growth of the technology caught the attention of Wall Street, as investors pile into shares of big tech companies, like Nvidia and Microsoft. A new generation of millennials and Gen Xers are pumping up these global mega cap tech stocks, while private artificial intelligence start-ups are infused by private equity and venture capital money. That interest has led to a dramatic outperformance in big tech shares.
Nvidia, which makes chips needed to power artificial intelligence technology, unveiled a sales and profit forecast on May 24, 2023 that far surpassed Wall Street expectations. The share price rocketed 28% higher after the bell to trade at $391.50, a record high. The gain added nearly $200 billion to its market capitalization, putting it in striking distance of $1 trillion – making it the world’s most valuable chipmaker. The strong forecast reflects “a steep increase in demand related to generative AI and large language models,” Nvidia Chief Financial Officer Colette Kress said on a conference call with analysts.
Shares of Nvidia and Facebook parent Meta more than doubled within the first six months of 2023. Microsoft, which in January announced a $10 billion investment in OpenAI, the startup behind ChatGPT, is up 39%. Apple, Google parent Alphabet and Amazon.com have each added more than 35%. These valuations are simply unrealistic: Nvidia trades at 49 times its forward earnings projection per The Wall Street Journal, while Microsoft and Meta trade at 31 and 20 times, respectively. My colleague Sam Horn wrote about the issue of outsized valuations in a prior blog, Value Investing Is Dead: Long Live Value Investing.
The “rapid growth” also caught the eye of the U.S. government. The push to regulate artificial intelligence could keep any noise building in the sector to a dull roar. In Congressional testimony, OpenAI founder Sam Altman warned the technology “could go quite wrong,” and fears abound that AI’s proliferation could eventually lead to lost jobs. And that says nothing for the potential crash of overhyped AI stocks… following in the footsteps of the meme frenzy or crypto craze.
Instead of playing into the hype with a riskier startup, look at companies with concrete products that can serve the AI market behind the scenes. Nvidia certainly qualifies, although it is massively overpriced. Strong alternatives capitalizing on AI momentum are companies like SK Hynix and Samsung Electronics (Polaris owns both companies as of 01/08/24).
SK Hynix has high bandwidth memory (HBM is stacked DRAM); it has existed for some time. But the true application of SK Hynix’s third- and fourth-generation HBM is AI because of the synergy and requirements needed to power Nvidia chips. On that front, SK Hynix currently has near 100% market share and they are the market leader. If you look at the normalized mid-cycle price-to-book value or P/E multiple or maintenance cash flow, SK Hynix is an obvious value stock.
Besides the obvious chip sales in artificial intelligence, Samsung has launched a new generative AI model designed for its devices. Currently used for Samsung employee productivity, the technology will be expanded to product applications… coming to a smartphone near you… While upfront plays like Microsoft, Samsung and SK Hynix may see a direct correlation between artificial intelligence and stock price, still others may gain a tangential boost.
Consider value play “derivatives” like U.S.-based Arrow Electronics or Avnet, Inc., both of which may be able to sell more AI-related electronic components in the heated market. MKS Instruments, Inc. could be another beneficiary, as more advanced chip technology requires more semiconductor equipment. Branching outside of pure tech plays, advertisers/marketers like Publicis and Interpublic could leverage more targeted AI advertising, while Science Applications International Corp. could capture more AI-related IT work. (Note: Polaris Capital owns the stocks listed in this paragraph as of 01/08/24)
Artificial intelligence has the power to enhance productivity, customer service and the quality of information delivered. It has the potential to redefine markets and industries; the difficulty stands in harnessing its power while mitigating inherent risks. From an investment standpoint, we believe the “behind the scenes” stocks have the best risk/return profile for this evolving industry.
This blog was penned by Ken Kim, Senior Investment Analyst, in January 2024. Mr. Kim joined Polaris as an Analyst in June 2016; he was promoted to Senior Investment Analyst in January 2021 and became an LLC member in January 2022. Mr. Kim collaborates with an experienced team of portfolio managers and analysts, all of whom are considered generalists, and perform fundamental bottom-up research.
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