Where Should Investors Begin?
Google CEO Sundar Pichai recently described the impact of artificial intelligence (AI) as “more profound than fire or electricity,” which left many investors asking how to invest and where to begin (1). Some would suspect to do so, it would take investments in start-ups or obscure corners of the technology industry. While venture capital is potentially one way to invest in AI, surprisingly, some of the biggest participants in AI are already represented within common large cap indexes such as the S&P 500. Companies within the technology, healthcare and data analytics sectors (to name a few) have been laying the groundwork for these technologies for many years. Below are some of the reasons why AI investments may be closer than you might think.
The Influence of Size
Large-cap companies such as Microsoft, Meta, Alphabet and Amazon, among others, have been investing in and building AI platforms for a number of years. For instance, Microsoft is a strategic investor in ChatGPT, which was born out of research that began in 2015 (OpenAI) and whose first model was launched in June 2018. In some instances, the time and capital poured into AI by companies may offer a head-start to making commercially viable products.
The research and development costs to build and run these programs can be significant. Some estimates put the cost to just run the servers necessary to power ChatGPT at $700,000 a day and is expected to rise given the higher degrees of sophistication and bigger datasets of future ChatGPT models. Larger businesses versus their smaller business peers (or start-up brethren) often have significantly more capital to invest and sustain these products while they are still early in development. Any burgeoning regulation around AI technology stands to benefit well capitalized companies as well, who have the resources to deal with the costs of complying with newer regulations. The current high interest rate environment is weighing on smaller companies and start-ups as well. Higher costs of lending money mean M&A and venture capital activity has slowed considerably over the past two years, making it harder for AI startups to acquire funding for the infrastructure or employees needed to scale their (2).
High-quality data is a fundamental cornerstone of AI, as it plays a critical role in training and refining algorithms. Companies which have amassed extensive datasets over time may have a substantial advantage over their less established counterparts. Tesla, for example, has accumulated billions of data points for its autonomous vehicles (and that is billions more than its next competitive rival), providing a wealth of information for enhancing their AI capabilities.
According to experts, ChatGPT-4 could include a staggering 170 trillion parameters (a 1,000x increase when compared to the ChatGPT version which exists today) (3). It is also not just clusters of information; Adobe is further developing Photoshop’s Generative AI product suite, helping users edit photos with a few clicks and a few words. Competitive advantages with data may serve as fuel which powers AI’s learning and decision-making capabilities.
The Power of Partnership
Unlocking AI is also likely to come through meaningful partnership and collaborations with non-AI companies. Such partnerships could have a wide reach and may touch essentially every sector of the economy. Recently, Wendy’s partnered with Google to evolve the customer drive-thru experience, which will include conversations with customers, the ability to understand made-to-order requests, and generated responses to frequently asked questions. Salesforce (CRM) rolled out Einstein GPT, which adds OpenAI’s features across its software platform. Salesforce and Accenture (ACN) are also teaming up to accelerate the deployment of generative AI across customer relationship management technologies. These partnerships are likely the first of many, as businesses consider ways which AI can help improve their offerings.
The growth of AI technologies and applications is an important consideration to the technology industry outlook, but investors would be remiss to not weigh the potential climate implications as well. While the technology industry typically scores well in terms of environmental risks, machine learning and AI models present a unique set of challenges in terms of resource consumption, particularly water. To train AI on a language model at the scale of ChatGPT, it requires the use of many state-of-the-art data centers, which require water to cool. Some early estimates put water consumption at up to 700,000 liters of water just for training purposes, with still more water required as the AI computes answers to user questions. This number could double or triple if the data centers involved are anything less than cutting edge in terms of water efficiency (4). While the benefits of this technology stand to be enormous in the long run, technology companies may begin to be flagged more often for environmental concerns if they fail in scaling their resource efficiencies accordingly with the needs of AI.
Investors may presume investing in new or emerging technologies would require investing in start-up businesses; however, in the case of AI, it is actually closer and more prevalent than investors might otherwise realize, as a number of large cap U.S. stocks, particularly those in the technology sector, already have a meaningful stake in the AI market. Therefore, investments in these already established large companies may offer exposure, albeit indirect, to the possibilities AI has to offer.
It is worth noting that, with the allure of exciting new products or technologies, an investing program does not come without risk, as there is a risk that the “losers” in this emerging space could outnumber a select few big “winners.” Individuals with interest in investing in AI should do so with caution and in the context of the overall investment portfolio and with one’s ability to bear risk.
Finally, Aswath Damodaran, Professor of Corporate Finance at NYU Stern School of Business, recently noted that investment returns are not simply made from AI gaining traction and integrating into our products and lives, companies must have a plan in place for the AI to generate returns. In essence, “even if we all agree that AI will change the way businesses and individuals behave in future years, there is no low-risk path for investors to monetize this belief.” (4). His perspective resonated with our own. As such, we are keeping a close eye on the AI opportunity set in line with portfolio objectives achieved through diversification, though positioned to benefit from this economic tailwind.
For more information, please contact any of the Professionals at Cedar Cove Wealth Partners.
- 60 Minutes: Google CEO: AI impact to be more profound than discovery of fire, electricity (4/16/2023)
- PWC – Global M&A Industry Trends: 2023 Mid-Year Update
- Medium: The Ultimate Guide to GPT-4 Parameters: Everything you need to know about NLP’sGame Changer.
- Making AI Less “Thirsty”: Uncovering and Addressing the Secret Water Footprint of AI models
- Musings on Markets – AI’s Winners, Losers and Wannabes: An NVIDIA Valuation , with the AI Boost! (6/23/2023)
- Artificial Intelligence (AI) is the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.
- ChatGPT stands for Chat Generative Pre-Trained Transformer, a language model based chat bot developed by OpenAI.
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