Our creations as humans have served to help us flow more easily through life. Think back to some of our first inventions: fire, stairs, and the wheel. Technological growth is an exponential one, which means that the rate of change of the exponential... is also exponential. You can think about exponentiality in time through a simple example, such as a population which has no carrying capacity. The rate at which the population increases is directly proportional to the size of the population itself. The rate at which technology increases is proportional to the level of technology, sure it took a long time to get from fire to the wheel, but how long did it take to get from the first phone to the iPhone X? The proof of exponentiality would be that it takes technology to make technology and the more technology you have for a starting point, the faster you can make new technologies. In theory... starting from no technology at all it would be impossible to create technology; so what was the spark? What was the turning point that turned us onto the course of this exponential technological growth?
If we look through nature, there is no species that can produce technologies even remotely close to ours. The question I think is important is what was that one little difference that made such an astronomical difference; what is the difference between our species and the most closely related species? This area of thinking can divide the arena of thought, and that is through religious viewpoints. Christians believe in intelligent creation by an intelligent creator, and more 'scientific' person would doubt such an idea and think it is not plausible or applicable to their problems; my attempt in writing is to help people realize that these ideas are not as different as you might think. We can all agree that nature and ourselves were made in an intelligent fashion, and the evidence for that is the beauty of nature. That little change that allowed homo sapiens to start on that exponential curve is still unknown, and the best we can do is guess to why it happened and what exactly happened.
Continue through the exponential advancements to today, where we have developed a systems that loosely mimics the frontal cortex, in order to recognize patterns. These types of systems are called machine learning or deep learning models. The models use neurons that are arranged either by a programmer or the model itself, that use training data to come to a conclusion about a new example. Deep learning models have been shown to greatly improve fields such as autonomous driving, data processing; and my favorite, natural language processing. The methods used to generate and 'understand' natural language are very focused on using as much power as possible to solve a problem. The current learning methods for NLP are analogous to solving a labyrinth by ramming through the whole thing with a bulldozer in an attempt to find the finish. We need to solve the labyrinth through develop an understanding of the labyrinth and how it works. After solving one labyrinth, maybe the machine could learn from its strategies to solve the first labyrinth and try to apply them to a completely separate labyrinth. The method for developing an understanding in a current DL system is very brainless and it may not be applicable to creating a solution that surpasses the previous one by an amount big enough.
Looking at things through an evolutionary perspective is extremely helpful. At its core, the questions, "What is the tipping point that made homo sapiens so much smarter than the last species?" and "What will be the tipping point between the AI we see right now and the next type of super smart AI that we all see in the movies?" Like I said earlier, something in our evolutionary history gave us the ability to grow faster than anything else in the history of the world, and it was essentially intelligence. Practically, the exponential growth of machine intelligence solely relies on the ability of machines to make intelligent updates to themselves. Exponentiality and random chance is the are the essences of creation, there must be a random chance to start that exponentiality but also, there must be some force to balance the exponentiality out, and those are problems. Look at a more realistic version of a population, lets say it is a population of rabbits. There is a restricted food supply, so therefore there cannot be billions or rabbits, there is a carrying capacity of k rabbits that the environment will allow. After the first two rabbits are created, it will start on an exponential path, but they will soon encounter the problem that there is not enough food to support all of the rabbits, so instead of the population following a pure exponential growth, it would follow a logistic type growth, where the rate of change of the population would equal zero and the population would equal k as time went to infinity.
I think the way we deal with problems in our lives is very similar to how nature works. Let's say we have a system of thinking that works well for us... until we encounter a problem that we are not equipped to deal with. We would find a solution to this problem, which would be very loosely analogous to the random chance principle, and this system helps us deal with our problem until we encounter a new one then we must create a new system of thinking. For humans there are multiple levels of dealing with problems, there is the level at which you create a solution for the problem at hand, then there is the level at which you try to create a solution that will help you deal with all problems. These levels of analysis exist on different levels of consciousness naturally even though they can both can be called into direct consciousness (thinking about it). The way to solve artificial general intelligence is not only to mimic the physical structure of the human brain, but to also implement one's understanding of psychology and philosophy into their models to create a more efficient design. That is why I speak from such a philosophical, psychological, and evolutionary perspective. There is defiantly something to be said for most of the great mathematicians being philosophers.