

Autopoietic Machine: is a technical system capable of regenerating, reproducing and maintaining itself by production, transformation and destruction of its components and the networks of processes downstream contained in them.
“The ongoing success of applied Artificial Intelligence and of cognitive simulation seems assured. However, strong AI, which aims to duplicate human intellectual abilities, remains controversial. The reputation of this area of research has been damaged over the years by exaggerated claims of success that have appeared both in the popular media and in the professional journals. At the present time, even an embodied system displaying the overall intelligence of a cockroach is proving elusive, let alone a system rivalling a human being.”
B. J. Copeland, May 2000, AlanTurin”The ongoing success of applied Artificial Intelligence and of cognitive simulation seems assured. However, strong AI, which aims to duplicate human intellectual abilities, remains controversial. The reputation of this area of research has been damaged over the years by exaggerated claims of success that have appeared both in the popular media and in the professional journals. At the present time, even an embodied system displaying the overall intelligence of a cockroach is proving elusive, let alone a system rivalling a human being.”g.net, Reference Articles on Turing (What is Artificial Intelligence? Is Strong AI Possible?)
While the statement captures the sentiment of many observers of the evolution of AI, much has changed however, to be more optimistic about this statement made by Jack Copeland, the author of books on the computing pioneer Alan Turing and who is responsible for identifying the concept of hypercomputation and machines more capable than Turing machines.
We have new insights into our understanding of information, its carriers, its processing, its communication, and its use in both living systems and in digital automata. We now understand how biological systems enable sentience (the ability to sense and respond), resilience (the capacity to recover quickly from non-deterministic difficulties arising from within or from outside without requiring a reboot) and intelligence (the ability to acquire and apply knowledge and skills). Our understanding stems from the lessons learned from different disciplines:
- The genome and the execution of the processes of living, neuroscience and the studies of cognitive behaviors,
- Digital automata with symbolic computing along with neural networks, which give us ways to unravel various mysteries about how our physical world works and to model, monitor and manage it, and
- The new mathematics of named sets, knowledge structures, cognizing agents and structural machines which allow us to not only explain how information processing structures play a key role in the physical world but also to design and implement systems which advance our current state of information technologies by transcending the limitations of classical computer science as we practice it today.
We now can model the information processing structures using the new mathematics and define their schema describing the autopoietic patterns contributing to sentience, resilience and intelligence. We argue that these patterns also allow us to design and implement a new class of digital autopoietic automata exhibiting sentience, resilience and intelligence at scale.
“While answering the question “Chicken or the egg, which came first?” it is said (Dyson, G. The Darwin Among the Machines: The evolution of Global Intelligence, Basic Books, New York, 1997, P 28.) that the chicken is an egg’s way of making another egg (or we can say replicating itself). The genes in the egg are programmed to replicate themselves using the resources available effectively. They already come with an “intent”, the workflows to execute the intent and monitoring and controlling best practices to adjust the course if deviations occur, whether they be from fluctuations in resources or the impact of its interaction with the environment. The intent of the genes, it seems, is the ability to survive and replicate. There is a symbiosis of the genes (which contain the information about the intent, workflows and also process knowledge to execute the intent) and the hardware in the form of chemicals such as amino acids and proteins that provide the means.”
Rao Mikkilineni, Giovanni Morana, and Mark Burgin. 2015. Oracles in Software Networks: A New Scientific and Technological Approach to Designing Self-Managing Distributed Computing Processes. In Proceedings of the 2015 European Conference on Software Architecture Workshops (ECSAW ’15). Association for Computing Machinery, New York, NY, USA, Article 11, 1–8. DOI:https://doi.org/10.1145/2797433.2797444
The purpose of this website is to share the knowledge about the theory and practice of autopoietic machines, without exaggerated claims.