Life is intelligence. Or, the application [for the significance] of being, for organisms, is intelligence. There are several factors that must be active for life to go on for a species. They include respiration, digestion, and so forth, but the difference that it means to be, against things that aren’t, is interwoven with intelligence.
There is no survival without intelligence. There is no participation in social groups [or for purposes] without intelligence. Intelligence is the reach [or advance] for organisms. So, what exactly is intelligence? What does it mean to be intelligent? This question, at least, for all organisms, describes: what does it mean to use what is known?
If an organism spots a predator, how does it become circumspect for evasion? If an organism spots prey, how does it trap it? What does it mean to move away from danger or move towards sustenance? The direct answer for intelligence is the use of what is known. Sometimes, intelligence is learned as memory, but generally, intelligence uses memory, even in novel ways.
While organisms are intelligent and have several other advantages, humans have exceeded them because human intelligence is far versatile. Human intelligence is extremely advanced, building societies that other organisms can’t seem to match.
Human Intelligence
How can human intelligence be defined and categorized? The only place to look is the brain. Other parts of the nervous system contribute, but the brain is where the buck stops. What is memory in the brain, and how is memory used?
In the brain, there are correlated components. Those components have attributes. The components and attributes can be used to define memory and then intelligence. Simply, there is no label in the brain for memory or for intelligence. Therefore, establishing this theoretically would mean identifying the components and then how they act for the labels that match memory, intelligence, and their variants.
While it is possible to explore several other options for memory and intelligence, the two most likely, conceptually, are the electrical and chemical signals of neurons. This means the components for memory and intelligence are electrical and chemical signals. Their attributes determine how they interact [or say how they are used, to result in intelligence].
Memory exists as configurations of electrical and chemical signals, conceptually. Intelligence [or the use of what is available at a destination] is relays and other attributes.
Attributes of signals, in sets, in clusters of neurons, include sequences, splits, relay summaries, reach residues, thick sets, and so forth. These can be used to explain how human intelligence works, especially when learning something new or during problem-solving.
Human Intelligence Research Lab
As artificial intelligence sprawls, it would answer several questions that human intelligence can provide. This means it will be able to use memory and apply significance to its availability, rivaling those with life. Also, since human intelligence is dominated by language, AI may broaden its reach for most aspects of valuable human intelligence.
For now, there is no human intelligence research lab anywhere in the world. The objective will be to have this lab display human intelligence, so as to grow options for parallels with how intelligence works to ensure that learning can be aided with better techniques, and then innovations can soar, locally, in societies, as well as creativity, towards better problem-solving.
This lab will become a major path to solutions, based on conceptual brain science. How does human intelligence get better at outcompeting AI?
There is a recent [August 26, 2025] story in The Transmitter, Long-standing theoretical neuroscience fellowship program loses financial support, stating that, “Funding from the Swartz and Sloan Foundations helped bring physicists and mathematicians into neuroscience for more than 30 years.”
There is a new [August 26, 2025] guest essay in The NYTimes, Students Hate Them. Universities Need Them. The Only Real Solution to the A.I. Cheating Crisis, stating that, ” If you ask students to use A.I. but critique what it spits out, they can generate the critique with A.I. If you give them A.I. tutors trained only to guide them, they can still use tools that just supply the answers. And detectors are too prone to false accusations of cheating and too poor at catching lightly edited output for professors to rely on them.”
“Learning is a change in long-term memory; that’s the biological correlate of what we do in the classroom. Now that most mental effort tied to writing is optional, we need new ways to require the work necessary for learning. That means moving away from take-home assignments and essays and toward in-class blue book essays, oral examinations, required office hours, and other assessments that call on students to demonstrate knowledge in real time.”
This article was written for WHN by David Stephen, who currently does research in conceptual brain science with a focus on the electrical and chemical signals for how they mechanize the human mind, with implications for mental health, disorders, neurotechnology, consciousness, learning, artificial intelligence, and nurture. He was a visiting scholar in medical entomology at the University of Illinois at Urbana-Champaign, IL. He did computer vision research at Rovira i Virgili University, Tarragona.
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