There's Plenty of Room Right Here: Biological Systems as Evolved, Overloaded, Multi-scale Machines (2212.10675v1)

Abstract: The applicability of computational models to the biological world is an active topic of debate. We argue that a useful path forward results from abandoning hard boundaries between categories and adopting an observer-dependent, pragmatic view. Such a view dissolves the contingent dichotomies driven by human cognitive biases (e.g., tendency to oversimplify) and prior technological limitations in favor of a more continuous, gradualist view necessitated by the study of evolution, developmental biology, and intelligent machines. Efforts to re-shape living systems for biomedical or bioengineering purposes require prediction and control of their function at multiple scales. This is challenging for many reasons, one of which is that living systems perform multiple functions in the same place at the same time. We refer to this as "polycomputing" - the ability of the same substrate to simultaneously compute different things. This ability is an important way in which living things are a kind of computer, but not the familiar, linear, deterministic kind; rather, living things are computers in the broad sense of computational materials as reported in the rapidly-growing physical computing literature. We argue that an observer-centered framework for the computations performed by evolved and designed systems will improve the understanding of meso-scale events, as it has already done at quantum and relativistic scales. Here, we review examples of biological and technological polycomputing, and develop the idea that overloading of different functions on the same hardware is an important design principle that helps understand and build both evolved and designed systems. Learning to hack existing polycomputing substrates, as well as evolve and design new ones, will have massive impacts on regenerative medicine, robotics, and computer engineering.

Biological Systems as Multi-scale Computing Machines

The paper "There's Plenty of Room Right Here: Biological Systems as Evolved, Overloaded, Multi-scale Machines," authored by Joshua Bongard and Michael Levin, explores the notion of biological entities as complex computational substrates through a concept they describe as polycomputing. The paper advocates for an observer-centered framework to perceive living systems as entities executing multiple computations within the same physical space and time. This perspective transcends the conventional cognitive biases and categorical limitations, traditionally imposed by technological and scientific models.

Polycomputing: Concept and Implications

Polycomputing is conceptualized as the capacity of a biological substrate to perform multiple computational tasks simultaneously. Unlike conventional deterministic computing systems, polycomputing implies that the intertwined complexities of biological systems allow them to perform various functions without clear segregation into singular tasks. The argument rests on a paradigm shift where computation is seen through a non-linear, stochastic, and more holistic lens, facilitating integration between computational science and biology.

A profound implication of embracing polycomputing is the potential to redefine the scope of fields like regenerative medicine, robotics, and bioengineering. By unraveling the underlying polycomputational properties of biological systems, novel synthetic polycomputational systems can be architected, offering new avenues for research and technology development. Bioengineers could design regenerative therapies or autonomous systems that utilize the inherent computational prowess observed in natural systems.

Exemplifying Polycomputing Through Nature and Technology

The paper provides compelling illustrations of natural polycomputing via examples like spider webs acting as both sensory and structural units, and neuronal networks storing multiple layers of memory states. By extension, technological parallels are drawn, such as physical reservoir computing, where materials are harnessed to perform logical operations using their intrinsic properties. These technological instances underscore the potential to build devices that concurrently fulfill multiple functions, akin to biological systems.

One striking case discussed is the evolutionarily conserved mechanisms allowing frog skin cells to exhibit behavioral plasticity — a phenomenon explored through the construction of Xenobots, small reconfigurable organisms with emergent behaviors not directly encoded within their genetic blueprints. This demonstrates polycomputing’s ability to transcend biological predicaments and adapt through structural and computational plasticity.

Moving Beyond Dichotomy: A New Philosophy of Computation

The authors challenge traditional machine paradigms by dissolving binaries, such as separating hardware from software and distinguishing life forms from machines. They advance a gradualist philosophy where the demarcation is blurred, proposing that computational definitions and life itself are contextual and observer-influenced. Therefore, identifying an entity as a computer relies significantly on the computational lens and framework applied by the observer.

Future Prospects in AI and Beyond

The paper hints at transformative prospects in AI and robotics through the polycomputing lens, illustrating how new computational architectures could enhance density and compatibility in biohybrid systems and mitigate issues such as catastrophic forgetting. Such advancements hold promise in developing systems that manage polyfunctional tasks in real-time, with enhanced cognitive and adaptive capabilities.

Concluding Remarks

Bongard and Levin’s exposition invites an overhaul of how biological systems are perceived and operationalized within the computational field. It elevates the dialogue between the life sciences and computational fields, envisioning an overview that is not bound by rigid definitions but receptive to the nuanced, overlapping functionalities observed in nature. Ultimately, this paper lays the groundwork for exploring the emergent computation-driven behavior in living systems, offering a pathway to harness these principles for innovative technological applications.