AI: The next frontier of exponential growth
“The greatest shortcoming of the human race is man’s inability to understand the exponential function.” – Allen Bartlett
According to ancient legend, chess was invented by Grand Vizier Sissa Ben Dahir around 6th century AD and given as a gift to King Shirham of India. The king was so delighted with the game that he offered him any reward he requested. With a caveat that it had to sound reasonable. The Grand Vizier had a modest sounding proposal: “Just one grain of rice on the first square of a chessboard. Then put two on the second square, four on the next, then eight, and continue, doubling the number of grains on each successive square, until every square on the chessboard is reached.”
King Shirham was baffled. Intuitively, it didn’t make sense. Why did this wise inventor ask such a modest reward for his wonderful game? Nevertheless, he immediately agreed. He ordered his treasurer to pay the agreed upon sum. During the first half of the chessboard, the tabulation of the reward was rather uninteresting. At first, the inventor was given spoonfuls of rice. Then bowls of rice. And then barrels. By the end of the first half of the chess board, the inventor had accumulated one large field’s worth or rice, or about 4 billion grains. At this point, the king started to take notice. As they moved through the second half of the chessboard, the situation rapidly worsened for the king.
One version of the story has the king going bankrupt as the 63 doublings, eventually totalled 18 quintillion (or million trillion!) grains of rice. At ten grains of rice per square inch, this requires rice fields covering twice the surface area of the Earth, including the oceans. Another version of the story has the inventor losing his head as punishment for this unreasonable request!
The story illustrates an important lesson: people are psychologically bad at dealing with exponential growth. Exponential growth shows an early stage of apparent inertia which it does not catch the eye. But suddenly, and completely unexpected, it arrives like a tsunami, flooding everything and everyone. In the real world, growing at an exponential rate is impossible for too long. There is not enough rice in the world to make such a massive payment based on accelerating growth! But those constraints are not as applicable in the digital world.
These days, computers and many other technologies are exponential, humans are not. This is where we see a lot of problems. Humans cannot predict the effects of exponential growth and cannot deal with the effects of it. We are constantly surprised by its speed. A more recent version of this chess tale is Moore’s Law. Gordon Moore, who recently passed away at age 94, was a pioneer in the semiconductor industry, the co-founder of Intel, and the originator of what came to be known as Moore’s Law. In 1965, he predicted that computing power would double every year. (Later amended to every second year.) “It sure is nice to be at the right place at the right time,” he told an interviewer in 2005. “I was very fortunate to get into the semiconductor industry in its infancy…from a time where we couldn’t make a single silicon transistor to the time where we put 1.7 billion of them on one chip.”
When it comes to technology, the second half of the chessboard is a phrase coined by futurist Ray Kurzweil, in reference to the point where an exponentially growing factor begins to have a significant economic impact on an organization’s overall business strategy. Today, we’re in the midst of another technological revolution based on artificial intelligence. Exponential change has been occurring for many years in AI, but it is only now because of the hype around ChatGPT, which can write human-like text and computer code, that AI has entered the public’s perception. The public is awakening to the very real possibility that these developments mark a “second half of the chessboard” moment.
Microsoft co-founder Bill Gates has said OpenAI’s GPT is the most revolutionary advance in technology since the microprocessor, the personal computer, the mobile phone and the Internet. He predicts that, due to the record-breaking speed of innovation, we will soon think of the pre-AI period in the same way some us might remember the blinking green cursor and having to first type C:> to work on a computer.
None of this means that innovation in AI won’t stumble from time-to-time or, as Gates puts it, “make factual mistakes and experience hallucinations.” Nevertheless, the technology will be transformative for individuals, businesses, and society at large. Currently, AI tools such as ChatGPT are trained to do a limited number of specific tasks. In the future, artificial general intelligence (AGI) will have the potential to learn any task or subject. On a mundane level, this could be like having the best personal assistant ever, or as Microsoft calls it, a co-pilot or personal agent, to write your emails, manage your inbox, and so forth.
Which brings us to investing. How will AI, and potentially AGI, transform businesses—both small and large? It’s impossible to predict, but Kurzweil himself noted, “I realize that most inventions fail not because the R&D department can’t get them to work, but because the timing is wrong—not all of the enabling factors are at play where they are needed. Inventing is a lot like surfing: you have to anticipate and catch the wave at just the right moment.” AI has had numerous false starts in the hype cycle over the last few decades, but it appears that many AI enabling factors are finally come into play which should feed into a sustaining positive feedback loop.
We are likely to see greater efficiencies and productivity as companies deploy AI in such areas as sales, customer service, manufacturing, finances, and various office functions. Many of the new business applications for AI tools may fall into use cases that are largely invisible to the public. These will not be the kinds of dazzling feats that garner media attention and the public’s fascination. They are more likely to be incremental improvements in productivity. Several of the businesses we own in our portfolios already use AI to increase efficiency and optimize productivity.
The deployment of large sums of investment dollars and resources is sure to speed up AI innovations. As humans, one thing we’re not so good at is understanding the potential effects of exponential change. With the acceleration and adoption of machine learning, the pace of innovation, and the magnitude of change, what happens after we cross to the other side of the chessboard is anyone’s guess. Where will we go from here—and at what speed? In the coming decade, AI may feel much like the last year’s Academy Award winning movie—Everything Everywhere All at Once. What a time to be alive!