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Criteria of strong thinking

In this world, intelligence deals with problems regarding inanimate objects, living beings, rational beings (people), organizations of these people, communities and societies in this world, as well as models of the world in humans and computers. Thinking here is quite activity-oriented and proactive: it involves the actions of people and robots and their organizations and communities with the world and models of the world. To think about something, you need to look at it, and for that, you need to turn your head. These actions of "turning your head and looking," and sometimes also "flying to the Moon and looking," or even "sending a robot to the Moon and observing it with its instruments," we also include in thinking. Thinking as proactive cognition includes the work of the body, as well as the exo-body.

Thinking is the behavior of the intellect when the intellect tries to find ways to solve problems that it has not encountered before. Thinking is practical/activity-based calculation/reasoning, which can lead to changes in the physical world. Intellect is the mastery of thought, a part of personality. Intellect is realized by the brain and body (embodied), or even by the brain working jointly with a computer (exocortex), body and tools (exobody) — a generalized computer-as-device, a "brain with eyes, ears, legs, arms, computers, and tools." We will call such a computer "creator" from now on. The computer mainly processes information based on some algorithms/knowledge from computation methods, while the creator processes information based on some algorithms/knowledge from methods and using tools/instruments/equipment, ultimately not only "reasoning" but also "acting," transforming the physical world. If we are talking about a part of the creator that implements the computational part of the algorithm, we call this workmanship in the method of operation. Intelligence is sometimes considered only as the skill of thinking, working with information about the surrounding world, and sometimes as the skill of changing the surrounding physical world (thus including not only the functions of creating practical methods but also the functions of the methods themselves). We will most often talk about intelligence as a skill operating with information/descriptions of the world to create other skills, and when it comes to changing the world, we will talk about the whole agent (including not only the personality consisting of numerous skills, including intelligence as part of these skills but also the organism/body with instruments). Nevertheless, a computer is also material, information processing occurs in the physical world.

We consider the intelligence::computer to consist of two parts:

  • Innate/hardware, determined by the biological characteristics of the human brain and body or the structural features of the computer hardware implementing artificial intelligence (AI). The brain and body provide intelligence with vast capabilities (compare human intelligence and that of a chimpanzee, a desktop calculator, and a data center with AI software), but they also significantly limit these capabilities (compare human intelligence on tasks like multiplying and dividing multi-digit numbers and an absolutely non-intelligent electronic calculator, whereas a well-trained artificial neural network also communicates fairly well but performs poorly in multiplying and dividing multi-digit numbers if not using a separate calculator program).
  • Acquired/software/“virtual computer” through immersion in human culture. This also applies to AI because AI learns from vast amounts of knowledge accumulated by human civilization; in more or less intellectual AI implementations, the emphasis is on compilations of texts with a total volume of tens of trillions of characters. This "learnable" part of intelligence includes fluent mastery of a limited set of thinking methods, having a surrounding physical world with its subjects.

We do not make assumptions about how intelligence is structured in its physical implementation, what parts of the brain and body it consists of, and how they are connected, although we speculate on the composition of the fundamental intelligence stack thinking methods. More details on this can be found in the first section of the “Intelligence Stack” course.

The ability to think using thinking methods from the basic intelligence stack distinguishes the intelligence of a modern highly educated person (not only a person, also AI) from the intelligence of a wild person or the intelligence of simple AI systems of previous generations. The "hardware" of intelligence in organisms titled professors at prestigious American universities and wild people from the jungles of the Amazon is the same. However, as explanations about how the world is structured accumulate, people (along with AI) have gained the ability to enhance intelligence through education: knowledge/explanations/thinking methods have changed, as well as the tools — now they do not think with a naked brain (just as they do not work with bare hands), they use modelers and other means to expand the brain's hardware capabilities.

The intelligence of an uneducated savage is significantly lower than the intelligence of an educated person precisely due to the lack of education in thinking methods of the intelligence stack. If the savage is educated, they will also become intelligent! Without education, the savage cannot quickly solve even a hundredth of the tasks that an educated person can solve. Moreover, an educated person will have time to apply tools to expedite problem-solving: laboratory equipment to collect experimental data, Google or ChatGPT to fill in missing knowledge.

The key word in the previous paragraph is “quickly,” as during problem-solving the savage could include the time of education gained by the educated person. If an educated person solves a problem in 10 minutes, the savage can solve the problem after 10 years of learning, plus the same 10 minutes. A significant part of intelligence is learned and can be enhanced instrumentally; only a small part of it is innate! This largely explains why a high IQ, as a measure of the capabilities of the biological brain for computations/reasoning, does not strongly influence performance in business, engineering, and science.