as humans continue to innovate, they push the frontier of knowledge progressively farther out. Consequently, each successive generation takes longer to reach the frontier, requiring more education and training to get there. As argued by economist Benjamin Jones, this growing “burden” is slowing innovation, as great inventors have less time to innovate.

Though there are innumerable reasons why the breakthroughs of the past 24 months are so startling, one of the most profound may be that AI feels no burden of knowledge.

Humans are the only species that pass significant knowledge from generation to generation. We rely on the wisdom of prior ages and build upon it. Only by using this information, by “standing on the shoulders of giants,” can we “see further” and innovate. This mechanism is the essence of progress.

Artificial intelligence, writ-large, does not suffer from the burden of knowledge. This technology does not die or degrade, it simply improves. Its relationship to knowledge acquisition raises profound questions: What will happen when it no longer needs us?

As artificial intelligence accelerates past us, it will accumulate knowledge we cannot comprehend.

Knowledge is a mountain that we are trying to tunnel through. It does not matter that the mountain does not, cannot, end, that we will not break through limestone one day and luxuriate in the sunlight of omniscience. Some believe such things happen in death, but no one expects life to deliver them. Still, we dig.

On a generational basis, animals make essentially no progress against the mountain of knowledge – they learn the same biological lessons over and over again.

Infected with the drive for knowledge and advancement, humans have a different relationship with the mountain of knowledge. Generation after generation, we tunnel further, learning more. We also tunnel differently: first, we used our hands, then a stick, then a tool, and now we sit on a rumbling chair, directing a vast and spinning drill.

“If I have seen farther, it is by standing on the shoulders of giants.”

Jones documents the result of this: the age at which notable inventions occur is significantly increasing. In 1900, for example, the peak ability to generate a great invention occurred at roughly 30 years old. By 2000, it had risen to nearly 40.

The more time it takes someone to reach the end of the tunnel, the less time they have to actually dig.

Because it does not die, there is no lag in reaching the rockface. Because it does not degrade, its digging does not slow. As our efforts decelerate, the Encephalon’s accelerate, and when it no longer needs us, it will be fully loosed in the mountain of knowledge, speeding ahead, leaving an ever-expanding gap between us and it.

No matter how complete your methodology or rigorous your training, you will not succeed in teaching a toad Archimedes’ principle, even as he plops into the water. In computing terms, these creatures are hardware-constrained, limited by their processing power. The Encephalon puts us in a similar position. We may become secondary creatures, incapable of understanding the world we live in, even as we reap its benefits. In such a configuration, we are the happy, wall-licking shih-tzu benefiting from central heating, ready food, and mesmerizing toys without grasping how they have arrived.

Durability is the greatest discrepancy now, but it will not be for long. Soon, we will be less capable, too. For a time, the wonders the Encephalon reveals could accelerate our learning, our tunneling; but without ancillary support, we will be outmatched.