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Natural and Artificial Concepts01:24

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In psychology, concepts can be divided into two categories: natural and artificial. Natural concepts are formed through direct or indirect experiences. For example, consider the concept of snow. If you live in a place with regular snowfall, such as Essex Junction, Vermont, you know snow through direct experiences. You’ve seen it fall, touched it, shoveled it, and played in it. You recognize its texture, appearance, and even its smell. In contrast, if you live on an island like Saint...
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The term "intelligence" is complex because it refers to both behavior and individuals, and its interpretation varies across cultures. European Americans tend to link intelligence with reasoning and cognitive skills, while in Kenya, it is tied to responsible participation in family and social life. In Uganda, intelligence is seen as the ability to know the right actions and carry them out effectively, while the Iatmul people of Papua New Guinea associate it with the capacity to remember...
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Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. One example of a machine is the cutting plier, which is used to cut wires by applying forces to its handles. When equal and opposite forces are exerted on the handles of the cutting plier, they cause the cutting edges to come together and apply equal and opposite reaction forces on the wire, which are greater than the applied forces.
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Cognitive psychology is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem-solving, as well as other cognitive processes. Cognitive psychology studies how information is processed and manipulated in remembering, thinking, and knowing.
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The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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在边缘安全人工智能.

Nader Sehatbakhsh1, Sudhakar Pamarti1, Vwani Roychowdhary1

  • 1Electrical and Computer Engineering Department, UCLA, Los Angeles, CA, USA.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
|January 16, 2025
PubMed
概括
此摘要是机器生成的。

尖端的先进传感器和人工智能 (AI) 通过整合传感和计算来模仿自然. 然而,这种方法引入了新的安全挑战,需要适应性学习系统来应对边缘AI中未知的攻击策略.

关键词:
人工智能的人工智能是人工智能.边缘计算是一种边缘计算.安全传感器安全传感器安全传感器系统性攻击是系统性攻击.

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科学领域:

  • 多式联络传感器技术多式联络传感器技术
  • 人工智能在边缘的边缘
  • 生物启发的计算是生物启发的.

背景情况:

  • 复杂的传感器和边缘的AI为复杂的系统提供了与自然竞争的潜力.
  • 目前的AI依赖于巨大的计算能力,不适合分布式系统.
  • 自然整合了计算,记忆和传感,以实时适应环境.

研究的目的:

  • 在集成边缘AI系统中定义系统性攻击类型.
  • 引入一个多层面的框架来打击这些攻击.
  • 提出适应性学习系统,以实时防御新型威胁.

主要方法:

  • 分析边缘人工智能系统中的安全漏洞.
  • 开发一个多层次的防御框架.
  • 探索低触摸适应性学习,以实时响应威胁.

主要成果:

  • 确定了针对集成边缘AI的独特系统性攻击向量.
  • 提出了一个新的多层次框架,以加强系统安全.
  • 强调了适应性学习的必要性,以防范未知的攻击策略.

结论:

  • 模仿自然的边缘人工智能系统需要新的安全范式.
  • 多尺度框架和适应性学习对于强大的安全性至关重要.
  • 未来的安全计算平台必须解决边缘人工智能安全的独特挑战.