Assembling non-biological materials (geomaterials) into a proto-organism constitutes a bridge between nonliving and living matter. In this paper we present a simple step-by-step route to assemble a proto-organism. Many pictures have been proposed to describe this transition within the origins of life and artificial life communities and more recently alternative pictures are emerging from advances in nanoscience and biotechnology. The proposed proto-organism lends itself to both traditions and defines a new picture based on a simple idea: Given a set of required functionalities, minimize the physicochemical structures that support these functionalities, and make sure that all structures self-assemble and mutually enhance each other’s existence. The result is the first, concrete rational design of a simple physicochemical system that integrates the key functionalities in a thermodynamically favorable manner as a lipid aggregate integrates proto-genes and a proto-metabolism. Under external pumping of free energy, the metabolic processes produce the required building blocks, and only specific gene sequences enhance the metabolic kinetics sufficiently for the whole system to survive. We propose a concrete experimental implementation of the proto-organism with a

Abstract. Ever since Alan Turing gave us a machine model of algorithmic computation, there have been questions about how widely it is applicable (some asked by Turing himself). Although the computer on our desk can be viewed in isolation as a Universal Turing Machine, there are many examples in nature of what looks like computation, but for which there is no well-understood model. In many areas, we have to come to terms with emergence not being clearly algorithmic. The positive side of this is the growth of new computational paradigms based on metaphors for natural phenomena, and the devising of very informative computer simulations got from copying nature. This talk is concerned with general questions such as: • Can natural computation, in its various forms, provide us with genuinely new ways of computing? • To what extent can natural processes be captured computationally? • Is there a universal model underlying these new paradigms?

Contemporary artificial life (also known as “ALife”) is an interdisciplinary study of life and life-like processes. Its two most important qualities are that it focuses on the essential rather than the contingent features of living systems and that it attempts to understand living systems by artificially synthesizing extremely simple forms of them. These two qualities are connected. By synthesizing simple systems that are very life-like and yet very unfamiliar, artificial life constructively explores the boundaries of what is possible for life. At the moment, artificial life uses three different kinds of synthetic methods. “Soft ” artificial life creates computer simulations or other purely digital constructions that exhibit life-like behavior. “Hard” artificial life produces hardware implementations of life-like systems. “Wet ” artificial life involves the creation of life-like systems in a laboratory using biochemical materials. Contemporary artificial life is vigorous and diverse. So this chapter’s first goal is to convey what artificial life is like. It first briefly reviews the history of artificial life and illustrates the current research thrusts in contemporary “soft”, “hard”, and

Rodney Brooks’ call for ‘new mathematics’ to revitalize the disciplines of artificial intelligence and artificial life can be answered by adaptation of what Adams has called ‘the informational turn in philosophy’ and by the novel perspectives that program gives into empirical studies of animal cognition and consciousness. Going backward from the necessary conditions communication theory imposes on cognition and consciousness to sufficient conditions for machine design is, however, an extraordinarily difficult engineering task. The most likely use of the first generations of conscious machines will be to model the various forms of psychopathology, since we have little or no understanding of how consciousness is stabilized in humans or other animals.

review articles doi:10.1145/2093548.2093569 Embodied and disembodied computing at the Turing Centenary.