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Opinion: AI on Wall Street Impacts Higher Ed on Main Street

Chip-maker Nvidia joined the trillion-dollar club recently, and it’s eyeing AI’s transformative potential in life sciences, physics, climate, cybersecurity, data science, robotics and simulation.

The top of a signpost against a blue sky, with two signs sticking off of it in either direction. The one on the right says "Wall Street" and hte one on the left says "Main Street."
While the effect of the dramatic growth of AI-related stocks on higher education may not be immediately apparent, there is a definite transformation occurring in the next generation of computing power for teaching, learning and research at universities and colleges worldwide. This digital transformation reaches across many academic disciplines and has the potential to make education more flexible and accessible to a much wider population.

While some people invest in individual stocks, many others have IRAs and 403(b) accounts and hope they grow long-term. Some investors may not be entirely aware of what individual stocks make up their portfolio. In the world of stock picks, one sector which has shown unprecedented growth is AI. There are many worthy companies making up this sector, but one stock has catapulted AI to a historical level both in price and function. Some experts have heralded this moment as an inflection point to rival the invention and implementation of the Internet. One company is particularly poised to redefine the current and future growth of AI: chip maker Nvidia, which Axios described last month as the potential “emergence of a new American corporate giant.”


Since May 2013, Nvidia has increased in value by over 10,000 percent. Second place on the top 10 list for stock growth over the last decade is Tesla with a “paltry” 2,800 percent increase. The real story, however, is what occurred in late May 2023 when Nvidia’s stock zoomed to a market capitalization of $1 trillion, joining the ranks of tech influencer giants Apple, Microsoft, Google and Amazon. This is a remarkable achievement for a chip designer and manufacturer. To get a sense of how much $1 trillion is, if you stack $1 bills, it will reach 68,000 miles — quite a view from space. Even seasoned investing commentors were surprised by the dramatic rise of this stock. As Luc Olinga wrote last week in the Clayton News Daily, “The blame game has begun about who saw and who didn’t see Nvidia coming. But that’s the wrong approach. No one did. No one has been able to predict AI becoming so disruptive in just a few months. The proof is that investors have thrown themselves into Nvidia shares like people starving for food.”

Nvidia CEO Jensen Huang said at a commencement ceremony last month at National Taiwan University, “Either you’re running for food, or you are running from being food.” Speaking at the recent Computex forum in Taipei, Huang claimed that anyone can become a computer programmer simply by speaking to a computer. Certainly, this points to the prospect of continued dynamic AI growth in new and unexpected areas.


So, what is the significance of this company? Nvidia is well known worldwide for designing and manufacturing graphic processing units (GPUs). Graphics cards from this company are on many computers today and are particularly important for gamers. It turns out these GPU chips are really good for machine learning and AI training models. This is an important inflection point for generative AI, which can produce a dizzying amount of content including text, images, audio, video and synthetic data which “is used as a stand-in for test data sets of production or operational data, to validate mathematical models and to train machine learning models,” as technical writer Kinza Yasar wrote in TechTarget.


Nvidia is not only poised to create explosive growth in the corporate sector but presents dramatic opportunities for higher education. The company has documented case studies which “Explore Limitless Learning in Academia.” On Nvidia’s website, the company suggests six areas in which AI has significant potential: life sciences, physics, climate, cybersecurity, robotics and simulation, and data science. AI will have a critical role particularly in STEM fields, but its influence will be even broader. M’hammed Abdous, associate director for faculty innovation at Old Dominion University, wrote in March that AI’s contributions to four areas are likely to shape our traditional educational environment, giving support for administrative, teaching, learning and research functions.


Powering AI applications requires a special chip, and Nvidia has an important one called the A100 which costs approximately $10,000. CNBC reported in February that “the A100 has become the ‘workhorse’ for artificial intelligence professionals now, said Nathan Benaich, an investor who publishes a newsletter and report covering the AI industry. Nvidia takes 95 percent of the market for graphics processors that can be used for machine learning, according to New Street Research.” Companies worldwide are eager for this special chip to run AI software applications like ChatGPT, multimedia tools and machine learning. Huge data centers will need these chips to create a multitude of AI-related processing. Nvidia is already shipping the next generation of AI chip, the H100 Hopper, with triple the performance at about three times the price. Large tech companies are planning to invest billions to integrate AI chips into their infrastructure. Writing in March for the computer publication Tom’s Hardware, in a piece called “ChatGPT Will Command More Than 30,000 Nvidia GPUs,” Zhiye Liu said, “Microsoft is in the process of integrating ChatGPT into Bing and Edge. Considering the size of the user base, Microsoft may have to spend billions to scale in the coming months and years.”


Nvidia is not alone in its AI quest. Google, Advanced Micro Devices (AMD) and Intel are all working on next-generation design and production of AI chips. While Microsoft has had a close relationship with Nvidia, in May 2023 it announced a collaboration with AMD on developing AI processors to accommodate the growing demand. AI company collaborations are likely to continue.


Investors typically want to see the AI hype continue to encourage more stock growth. However, thought leaders are talking about a much slower approach. Christina Pazzanese, staff writer for the Harvard Gazette, wrote in 2020 about the ethical concerns of AI in privacy and surveillance, bias and discrimination, and the role of human judgment. In her article, she quoted political philosopher Michael Sandel: “Can smart machines outthink us, or are certain elements of human judgment indispensable in deciding some of the most important things in life?”

The role of higher ed may be to carefully utilize the impressive tools AI provides and question the ethical implications it brings. As with investing, it is prudent to understand both the rewards and the risks. Wall Street may very well be paving the way, yet higher ed on Main Street might be able to provide helpful guardrails and speed limits for a productive and safer technology community.
Jim Jorstad is Senior Fellow for the Center for Digital Education and the Center for Digital Government. He is a retired emeritus interim CIO and Cyber Security Designee for the Chancellor’s Office at the University of Wisconsin-La Crosse. He served in leadership roles as director of IT client services, academic technologies and media services, providing services to over 1,500 staff and 10,000 students. Jim has experience in IT operations, teaching and learning, and social media strategy. His work has appeared on CNN, MSNBC, Forbes and NPR, and he is a recipient of the 2013 CNN iReport Spirit Award. Jim is an EDUCAUSE Leading Change Fellow and was chosen as one of the Top 30 Media Producers in the U.S.