The intelligent things may not always be complex, but a critical level of complexity is required for intelligence to appear.
Complexity is a property of intelligence. It seems that a critical level of complexity is required for the intelligence to appear. This is where compression (that can be thought as the ability to infer OR simplify OR express OR reduce complexity) comes to the scene. The problem of compression is the same problem of AI in many aspects. Complexity analysis can be used to measure the change at the performance of the business when you apply changes in the processes of the business or in its portfolio of products. As complexity and innovation are related to functionality, complexity analysis can be used as a technique to manage innovation. This is an attempt to innovate inside the innovation management field. To innovate, you must have the right environment and mental peace - fail, retry and retry until a breakthrough "suddenly" happens.
Genius and intelligence are related to innovation. As innovators are someone who can let his/her mind "free" of constraints (education, technology) in the environment in which you can stimulate the "invisible" by spurring creativity through a sounding board resonance or vibration. , and innovation is related to technique, the great artists used different techniques, Monet used a style called impressionism, which involved color matching and mixing to achieve the desired effect. Georges Seurat used dots to make a picture. Tiny dots give rise to a picture. Many dimensions could exist like the dots, but unless you view them in groups or a combination, it’s hard to see the big picture or give credence to the existence. Einstein was not an artist, but he was a great innovator.
Intelligence is mainly comprised of two parts. The first part is the brain ability to preliminarily understand the extent of any problem or condition. The people with what being referred as highly intelligent have a strong aptitude to understand the "complexity" of the given problem. It's like a rating scale of complexity. Some people get the whole picture as opposed to others that can't seem to get a grasp on the problem. Now the second part to intelligence is the brain's ability to call on as many neural circuits and work with as many areas in the brain it needs to solve the given problem. In order to get "intelligence", a brain (a dynamic, evolving network of interconnected neurons) must have a certain minimum amount of complexity (complexity is a function of structure, the topology of that network of neurons, and entropy).
Consider intelligence as a mechanism; it lets one to divide the problem into different parts in order to understand its foundations better. Intelligence is the ability to break any complex thought or problem to the most rudimentary parts whereas they either can be acted on or dismissed. It is the level of activity in either case or the means of which activity or lack of activity or alternatives that demonstrate levels of intelligence. Then where does the complexity manifest itself in the intelligence process? What being considered intelligence is a very complex system indeed, and, therefore, is not very amenable to modeling as many scientists have tried to model it and the human brain, have seen the extreme difficulty in doing so.