Abstract
The original computers were people using algorithms to get mathematical results such as rocket trajectories. After the invention of the digital computer, brains have been widely understood through analogies with computers and now artificial neural networks, which have strengths and drawbacks. We define and examine a new kind of computation better adapted to biological systems, called biological computation, a natural adaptation of mechanistic physical computation. Nervous systems are of course biological computers, and we focus on some edge cases of biological computing, hearts and flytraps. The heart has about the computing power of a slug, and much of its computing happens outside of its forty thousand neurons. The flytrap has about the computing power of a lobster ganglion. This account advances fundamental debates in neuroscience by illustrating ways that classical computability theory can miss complexities of biology. By this reframing of computation, we make way for resolving the disconnect between human and machine learning.
Highlights
The most celebrated biological computing system may be the brain, and it is widely believed to be performing various kinds of computations, but exactly which kinds of computations we do not fully understand
Kirkpatrick computing systems have processes that are not computational in any sense, and processes that intertwine with computational functions to augment the computational space in a way that digital computers and robots cannot do—and might not ever be able to do until we formulate new ways of making computational systems
Among various accounts of computation, especially the excellent mechanistic account of physical computation which is useful for analyzing computing artifacts, computational functions are usually distinguished from non-computational functions [5]
Summary
The most celebrated biological computing system may be the brain, and it is widely believed to be performing various kinds of computations, but exactly which kinds of computations we do not fully understand. But it is reasonable to interpret his writing as saying that definite physical effects are significant effects that are not Turing machine effects: erasing or writing digits, moving the head left or right, or changing the internal state To link this to mechanistic physical computation, it should be recognized that computation is not the same concept as information processing, but that processing information entails generic computation, not necessarily digital computation [3, 5]. The mechanistic account of physical computation comes close to articulating the particular abilities of biological computing systems, after some subtle modifications into a new account which we will call “biological computation.” This will be closer to a new model of computation that encompasses both action and traditional computation The mechanistic account of physical computation comes close to articulating the particular abilities of biological computing systems, after some subtle modifications into a new account which we will call “biological computation.” This will be closer to a new model of computation that encompasses both action and traditional computation
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