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Natural Computation

How does biology do information processing? Four billion years of nature’s own R&D has produced highly robust, fault tolerant, adaptive, dynamic and complex biological information processing systems with truly astonishing capabilities well beyond the capabilities of human-engineered information processing systems (today’s computers).

There are good grounds for believing that there is still much to be discovered and learned that could fundamentally revolutionise computing from studying and understanding how biology does it and how nature’s own R&D created such systems.

Moreover, might it be possible not only build far more powerful computers using some of the lessons from how biology does information processing and computation, but do computing that is orders of magnitude more powerful than is possible with silicon and software as we define it today, directly with biology itself?

We are embarking on a long-range research programme at the interface of biology, chemistry, engineering and information technology exploring these issues. Specifically, we will be focusing on two key directions:

  1. Nature-inspired computation: what can we learn from biological information processing to develop powerful new algorithms and software, and computing hardware?
  2. Biological computing: is it possible to build entirely new kinds of powerful general purpose computers out of biological components and systems, and if so, what do we need to know about biology and biological information processing in order to even begin to start to build such computers?

Our work in this field is just beginning.

Grand Challenges in Non-Classical Computation

We started our endeavour by co-organising with the University of York the first international workshop on "The Grand Challenges in Non-Classical Computation" in York in April 2005.

The Grand Challenge is a long-term research aspiration that seeks to explore, generalise, and unify all the many diverse non-classical computational paradigms (including bio-inspired computation, open complex adaptive systems, emergent systems, quantum and other non-classical physics computing), to produce a fully mature and rich science of all forms of computation, that unifies the classical and non-classical (natural) computational paradigms. The aims of this workshop were to assemble a number of key people in the non-classical computation field to facilitate discussion and debate, discuss and evaluate the importance of an inter-disciplinary approach to developing future novel computational architectures and discuss and define what future generations of novel ‘computational building blocks’ may involve.