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制造“面包”:当下及未来人工智能的仿生策略

Making BREAD: Biomimetic Strategies for Artificial Intelligence Now and in the Future.

作者信息

Krichmar Jeffrey L, Severa William, Khan Muhammad S, Olds James L

机构信息

Departments of Cognitive Sciences and Computer Science, University of California, Irvine, Irvine, CA, United States.

Sandia National Laboratories, Data-Driven and Neural Computing, Albuquerque, NM, United States.

出版信息

Front Neurosci. 2019 Jun 27;13:666. doi: 10.3389/fnins.2019.00666. eCollection 2019.

Abstract

The Artificial Intelligence (AI) revolution foretold of during the 1960s is well underway in the second decade of the twenty first century. Its period of phenomenal growth likely lies ahead. AI-operated machines and technologies will extend the reach of Homo sapiens far beyond the biological constraints imposed by evolution: outwards further into deep space, as well as inwards into the nano-world of DNA sequences and relevant medical applications. And yet, we believe, there are crucial lessons that biology can offer that will enable a prosperous future for AI. For machines in general, and for AI's especially, operating over extended periods or in extreme environments will require energy usage orders of magnitudes more efficient than exists today. In many operational environments, energy sources will be constrained. The AI's design and function may be dependent upon the type of energy source, as well as its availability and accessibility. Any plans for AI devices operating in a challenging environment must begin with the question of how they are powered, where fuel is located, how energy is stored and made available to the machine, and how long the machine can operate on specific energy units. While one of the key advantages of AI use is to reduce the dimensionality of a complex problem, the fact remains that some energy is required for functionality. Hence, the materials and technologies that provide the needed energy represent a critical challenge toward future use scenarios of AI and should be integrated into their design. Here we look to the brain and other aspects of biology as inspiration for Biomimetic Research for Energy-efficient AI Designs (BREAD).

摘要

20世纪60年代就已预言的人工智能(AI)革命,在21世纪的第二个十年正全面展开。其显著增长的时期可能还在前方。人工智能操控的机器和技术将把智人的活动范围扩展到远远超出进化所施加的生物限制:向外深入到深空,以及向内进入DNA序列的纳米世界和相关医学应用领域。然而,我们相信,生物学能提供关键的经验教训,从而为人工智能带来繁荣的未来。一般而言,对于机器,尤其是人工智能来说,长时间运行或在极端环境中运行将需要比目前高效几个数量级的能源使用效率。在许多运行环境中,能源将受到限制。人工智能的设计和功能可能取决于能源的类型及其可用性和可获取性。任何在具有挑战性的环境中运行人工智能设备的计划都必须从它们如何供电、燃料位于何处、能量如何存储并提供给机器,以及机器在特定能量单位下能运行多长时间这些问题开始。虽然使用人工智能的一个关键优势是降低复杂问题的维度,但事实仍然是,功能实现需要一些能量。因此,提供所需能量的材料和技术是人工智能未来应用场景面临的一项关键挑战,应将其纳入人工智能的设计中。在此,我们将大脑和生物学的其他方面视为仿生研究以实现节能人工智能设计(BREAD)的灵感来源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b66d/6610536/b2deb87e1df6/fnins-13-00666-g0001.jpg

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