Investors have not seen a transition where the winners of the last cycle are the winners of the next cycle. Will AI break the paradigm?
Reston, VA – Mason Investment Advisory Services, Inc. hosted members of the US Large-Cap Growth Equity Strategy team from T. Rowe Price for a discussion of how developments in artificial intelligence could lead to opportunities for investors to benefit.
“AI is one of the [rarest] innovations where the larger you are and the larger data sets you have, your ability to actually provide better algorithms goes up,” said Taymour Tamaddon, portfolio manager of the US Large-Cap Growth Equity Strategy in the U.S. Equity Division.
Tamaddon incorporates insights gained from analysis and meetings with leadership of technology companies into his team’s stock selection process. Mason clients benefit directly from these insights.
The term “artificial intelligence” was originally coined in 1956 when a small group of scientists – including mathematicians, computer engineers, physicists and psychologists – convened at Dartmouth University for the Summer Research Project on Artificial Intelligence.
The project was “to proceed on the basis of the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it,” according to the university’s website.
Today, AI applications can summarize articles, write stories, translate, predict and generate text as well as other forms of content, such as images or computer code or even protein or molecular sequences. Perhaps the best known example is the text generating application ChatGPT, which launched to the public in November 2022.
Each AI application is powered by a large language model (LLM), a deep learning algorithm that houses an artificial neural network of computer parameters constructed using the same principles as a biological brain. Just as a biological brain learns by absorbing information from the outside world, the LLM algorithm learns by absorbing enormous amounts of data.
“It’s really hard now to leapfrog software and data advantages, because what drives people to choose certain products, services or software is not necessarily just a better product,” Tamaddon said. “It’s output of the product.”
The more data, the more efficient and powerful LLMs can become, which is one reason large-cap companies may be better positioned to capitalize on AI applications now and in the future, Tamaddon said.
Applications of AI extend far beyond predictive text used for chatbots or translators. The same technology is creating new possibilities in fields such as insurance, law, health care, life sciences, natural sciences, software, microchips, robotics, financial services and more.
The expectation is that AI will unlock a new wave of research, creativity and productivity while helping to generate complex solutions for the world’s toughest problems, according to the NVIDIA blog.
For investors and money managers, the path to consistent or big wins for portfolios could prove tougher, Tamaddon said, because there are no small companies that are known and positioned to disrupt larger ones, who own more data and can implement plans to monetize said data.
“It’s not just the data that makes a company […] likely to be a continued winner over the next five years, it’s [that company’s] ability to monetize AI,” Tamaddon said. “That’s just a meaningful differentiator.”
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