Computing: What Does it Mean to be Human? Intelligence? AI has a path.

Some people are waiting for superintelligence or making broad comparisons to indicate that artificial intelligence is not close to humans. However, they miss a central measure of what human intelligence comprises.

Human intelligence is simply the specialness of usage of human memory. Or, intelligence is the quality of usage of memory in any system. Memory is comparably cheap and easy. Intelligence is rare and had been in the domain of organisms alone, with humans at the top, until recent years.

Books have memory, but they are not intelligent because they cannot use the memory. Walls, sculptures, scrolls, footprints, paintings, and so on, are all forms of memories that only enable intelligence for external usefulness [organisms], not internal.

Digital has memory. The memory is accurate and dynamic—with audio and videos—aside from texts and images. This memory, for decades, only provided for external intelligence, like those of other non-organisms, until machine learning came along.

All digital memory is data, with a fundamental unit as bits—in binary. This means that anything digital has a binary equivalent. Anything binary is convertible to other types of digits including the [common] denary—or numbers in base ten. Being digits, evaluations for patterns, outputs, conditions, minimums, maximums, averages, differences, and so forth are possible. So, it is feasible to take those numbers and fit them into new arrays or equivalence, differently from their original.

Simply, it is possible to straddle data on lines of options—with equations—to match new output types, corresponding usefully to versatile images, texts, video and audio patterns, with several examples in the set. This means obtaining something different from similar examples is mathematically possible for data. The result may then match the same intelligence in the original data—in new ways. Mathematical equations are summarily the channels to use what is in digital memory to result in intelligence—even if ‘it does not understand like humans.’

In the human mind, memories abound. There are also relays—or distributions—across memory destinations to select for outputs with relevance. What makes humans more intelligent than other organisms is the variations of relays across memory areas. When an expert is speaking from an experience, it is relays across memory. When an individual connects the dots—or figures something out—it is relays across memory. Relays across memory are more vital to intelligence than embodiment. Several organisms have the same environments as humans, yet they do not maximize them due to deficits in relays.

Intelligence is how memory is used. The better memory is used—by relays, the better anything is intelligent. There are several tangential ways to describe intelligence, but at the source it is mechanized or the human mind, relays hold sway. Large language models [LLMs] have an important relay across data—prediction. This relay can reproduce intelligence in new ways that can match answers like those relayed in the human mind. There would likely be new directions with which relays would be possible for digital memory, resulting in better artificial intelligence.

However, the current possibility for relays across digital memory shows that what makes humans intelligent is already available with machines. And intelligence is not just a mind, or a life, or even sentience, but the difference between humans and other organisms. AI is using a key domain of human intelligence—language—with relays that are sometimes accurate. Humans may no longer be alone, as the highest intelligence, based on relays that can sometimes equal human productivity and outputs. Simply, what makes humans exceptional? Intelligence, not just bigger brains. What makes human intelligence possible? Relays quality across memory destinations. If digital memory—made and stuffed by humans—has additional quality relays of memory, can it match or surpass human intelligence? Maybe. What can humans do about it or how can humans prepare is a better question than dismissing the the likelihood of AI advance.

There is a recent open question in The New Yorker, In the Age of A.I., What Makes People Unique?, stating that, “It’s hard because human life is elusive, variable, and individual, and also because characterizing human experience pushes us to the edges of our own expressive abilities. And so, probably, the polarity of our conversations about A.I. should be reversed. Instead of assuming that we know what human beings do, we should presume that, whenever an A.I. replaces a person in some role or other, something—perhaps a great deal—is lost. We should see the abilities of an A.I. as powerful, but never really humanlike. We should grow newly comfortable with asserting that human nature is indispensable, and take pride in the fact that we must struggle to define it.”

There is a recent review on Spiked, Will AI redefine what it means to be human? stating that, “In any case, comparisons between human intelligence and AI are always misleading. Human brains do not simply process information as computers do. The mind is not just software running on the hardware of the brain. Human intelligence is an ever-expanding, ongoing, open-ended and fundamentally social process. It is rooted in the cultural practices, emotions, morals and knowledge we have created and passed on over generations. Nowadays, the risible idea that the unconscious machines we have created will soon come to dominate us is tragically widespread. This is more a symptom of our anti-human zeitgeist than it is proof for AI’s ‘superior’ intelligence. It is a product of a deterministic, fatalistic culture of lowered expectations, in which human beings are no longer viewed as autonomous, history-making subjects”

There is a recent story on ABC7 Chicago, New technology at Argonne National Laboratory in Illinois transforms scientific discoveries, stating that, “Together, the two cutting-edge scientific instruments are poised to revolutionize research across a wide range of fields, from materials science and medicine to climate modeling and energy. This year, Argonne, the federally funded research and development center in Lemont, Illinois, is ramping up usage of the two dynamic scientific tools. Aurora was introduced earlier in 2024, while the APS was launched this year, as well. Aurora was fully installed at Argonne in 2023. One of the world’s most powerful supercomputers, it is capable of performing over a quintillion calculations per second. This spring, Argonne announced that it broke the exascale barrier, and is now the fastest and highest-ranked supercomputer in the world for high performance computing and artificial intelligence convergence. The APS, which is housed in a ring so large that Wrigley Field could fit in its entirety inside, will generate X-rays that are up to 10 times brighter than its predecessor, allowing scientists to study matter at unprecedented levels of detail. By combining the capabilities of Aurora and the APS, researchers will be able to investigate the structure and properties of materials with unprecedented precision.”