一个以蝶为灵感的多感官神经形态平台,用于整合视觉和化学线索
Yikai Zheng1, Subir Ghosh1, Saptarshi Das1,2,3,4
1Engineering Science and Mechanics, Penn State University, University Park, PA, 16802, USA.
Advanced materials (Deerfield Beach, Fla.)
|December 9, 2023
概括
这项研究介绍了一种新的人工智能 (AI) 多感官平台,集成视觉和化学感官. 灵感来自蝶交配行为,它增强了机器人和神经形态计算的决策.
科学领域:
- 神经形态计算是一种神经形态计算.
- 材料科学 材料科学 材料科学
- 人工智能的人工智能
背景情况:
- 动物依赖多感官集成来生存和繁殖,但人工智能和神经形态系统主要处理单感官数据.
- 开发多感应人工智能的关键局限性是缺乏小型化硬件,能够同时定位多种传感器并实现传感器内处理.
研究的目的:
- 开发一个微型硬件平台用于视觉化学集成,解决当前AI和神经形态计算的局限性.
- 创建一个生物灵感系统,模仿Heliconius蝶的伴侣选择,以提高决策能力.
主要方法:
- 利用石墨烯用于化疗传感和单层二硫化物 (MoS) 用于光传感,以创建混合多传感平台.
- 利用MoS2传感器的内存计算能力来设计用于决策的神经电路.
- 在蝶Heliconius的伴侣选择过程中建模了该系统,该过程整合了视觉和化学线索.
主要成果:
- 成功创建了一个功能性的多传感平台,能够进行视觉化学集成.
- 展示了传感器内和近传感器处理的潜力,以增强感知体验和决策.
- 开发了使用MoS memtransistor的神经电路,以实现高效的多感官数据处理.
结论:
- 开发的灵感来自蝶的平台超越了单感官人工智能,实现了复杂的多感官决策.
- 这种视觉化学集成平台对机器人技术和神经形态计算的未来有重大影响.
- 该研究强调了像石墨烯和MoS这样的新材料在创建先进的人工智能硬件方面的潜力.
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