Intelligent Life

By november 27, 2018 april 8th, 2019 Algemeen

With networks, we can organize and integrate information at different levels. On a biological level, our bodies are made up of many networks that are integrated at and communicating on multiple scales. From our genome to the molecules and cells that makeup the organs in our bodies all the way out to ourselves in our world: we are fundamentally a network of networks. Living organisms are, in essence, complex systems which process information using a combination of hardware and software. Over time, people figured this out and started to use natural systems as inspiration for efficient solutions. If we listen to what nature is telling to us, we can take better decisions, build more sustainable buildings, create systems that function where and when we need them to, all in one, assign nature solution to human problems. Nature is an ecosystem made from living organisms like us humans.

In thriving living systems, the entire process of divergence, relationship and convergence is self-organizing, set into motion by life itself. In the dynamic, moment-by-moment interplay of divergent parts coming together to create a sufficiently convergent whole, supported and connected by  a consistent yet adaptive relational and governing infrastructure, all animated and guided by the self-organizing spark of life. By this the living system is able to self-organize in order not only to persist but to adapt and ultimately to generate higher, more complex forms of life. Without the spark of life, these outcomes are impossible. With it, the paradox of diversity within unity is reconciled naturally and effortlessly in living systems, generating resilience, innovation and even beauty.

The generation of design (configuration, patterns, geometry, shape, structure, rhythm) in nature is a physical phenomenon that unites all animate and inanimate systems. Design in Nature always shows itself as systems that flow and improve themselves. Systems improve themselves because the movement from chaos to order takes many discrete steps. Nature creates and operates it’s systems efficiently. Natural processes and nature’s problem-solving methods emanate originality, precision, and incredible utilization of resources. It is no wonder why we always return to them when everything else fails or when we are in need of an excellent solution. The natural world is the most adaptable complex system ever known to humans. Evolution provides us with countless examples of systems performing various types of computations. We harnessed some of these ideas and created artificial systems comparable with natural ones, like optimization algorithms inspired by ant colonies This type of probabilistic models is useful for finding optimal solutions for situations encountered in operations management, like the shortest path problem, combinatorics problems in resource allocation, multi-objective optimization problems.

The natural world has always designed intelligent systems. Chemical networks, cells, our brain, or our societies are examples of adaptive and autonomous systems. Everywhere you look, the natural world bursts with examples of complex adaptive systems. However, nature has a significant advantage on its side: time. The majority of these systems are the result of years and years of evolution. Years during which they went from one configuration to the next until they found the best way to solve the task. Fair enough, sometimes constraints prevented a natural system from finding the best solution. Those situations had catastrophic consequences such as the extinction of a species or the loss of a large number of members of a population. Technology does not have the luxury of perfecting a solution over millions of years nor can we afford catastrophes. With all their differences, nature and technology should not be excluding each other. We should pay close attention to the natural world. Start by finding out if a biological system has not already solved the problem. If it has, then there is no point in reinventing the wheel, extract the fundamental principles and methods and transfer them to the problem we are trying to solve. Nature is a source of inspiration, while technology is the engine for creation. Artificial Intelligence (AI) is closely related to biology, neuroscience, or cognitive science. Scientists and practitioners borrowed many ideas from the natural world about computation. AI algorithms and in some instance entire fields derive from biological systems. For example, neural networks use elements from the architecture of the brain. Moreover, we have optimization algorithms inspired by natural evolution, ant colonies, or immune systems. Thus, AI and the natural world share many similarities.

So AI is closer to us then we might think as AI seeks to design and build computational systems that can reason, sense, and make decisions in complex environments and under much uncertainty. The connection between artificial intelligence and nature helps to create advanced technologies. Understanding the processes behind any form of intelligence occurring in the animated world will reshape business  and industrial processes.

Developments in artificial intelligence relate to biological and the natural world. Many algorithms and systems inspired by systems found in nature have been developed: evolutionary algorithms, artificial neural networks computational immunity systems, bio-robotics, swarm intelligence or optimization algorithms based on colonies, hives, or flocks. These ideas transformed how we develop new technologies and solve problems. Bio-inspired solutions benefit from the fact that nature has already refined a lot of the steps to make them as efficient as possible. Thus, by this we are able to develop disruptive technologies by combining engineering and natures fine-tuned solutions.

But, we should seek to act as wise, compassionate stewards of life — our own lives and all life. Only with these intentions can we be trusted to self-govern. And only with this guidance we can proceed in our technological drive.

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