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相关概念视频

Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

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An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
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Distribution Reliability and Automation01:25

Distribution Reliability and Automation

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Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
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Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
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Avoidance Learning and Learned Helplessness01:14

Avoidance Learning and Learned Helplessness

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Avoidance learning and learned helplessness are critical concepts in understanding behavioral responses to negative stimuli.
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Neural Regulation01:37

Neural Regulation

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Digestion begins with a cephalic phase that prepares the digestive system to receive food. When our brain processes visual or olfactory information about food, it triggers impulses in the cranial nerves innervating the salivary glands and stomach to prepare for food.
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Uncertainty: Overview00:59

Uncertainty: Overview

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In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
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相关实验视频

Updated: Sep 19, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

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生成性AI网络安全和弹性

Petar Radanliev1,2, Omar Santos3, Uchenna Daniel Ani4

  • 1Department of Computer Sciences, University of Oxford, Oxford, United Kingdom.

Frontiers in artificial intelligence
|June 18, 2025
PubMed
概括
此摘要是机器生成的。

生成型人工智能 (AI) 提供强大的内容合成,但存在重大伦理和安全风险. 这项研究突出了快速采用人工智能和治理之间的差距,敦促针对负责任的人工智能部署制定适应性,特定部门的战略.

关键词:
网络安全 网络安全数据伦理学数据伦理学生成型的人工智能 (GAI)政策发展政策的发展.负责的人工智能部署部署影子AI是一种人工智能.

相关实验视频

Last Updated: Sep 19, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

693

科学领域:

  • 计算机科学与工程 计算机科学与工程
  • 信息科学 信息科学 信息科学
  • 网络安全和伦理学

背景情况:

  • 生成型人工智能 (AI) 系统能够在不同领域自主创建内容,这代表了机器学习的重大进步.
  • 生成型人工智能的快速发展和部署带来了大量的伦理,安全和隐私挑战,目前的治理框架都在努力解决这些挑战.
  • 现有的社会技术和治理模型需要适应,以有效地管理先进的人工智能技术的影响.

研究的目的:

  • 系统地调查生成性AI部署所带来的伦理,安全和隐私挑战.
  • 开发一个综合的理论框架,用于评估和指导在整个生命周期中对生成人工智能的负责任应用.
  • 确定生成性人工智能采用和机构保障成熟度之间的断开,并提出适应性治理解决方案.

主要方法:

  • 在PRISMA的指导下进行了一次系统的文献审查,以收集有关生成AI挑战的相关研究.
  • 采用专题和定量分析来调查生成性AI的社会技术影响.
  • 开发了一个综合的理论框架,借鉴技术采用,网络安全弹性和规范治理模型.

主要成果:

  • 在生成性人工智能系统的快速采用和成熟的机构保障措施的发展之间存在很大的差距.
  • 新的风险,包括与"影子人工智能"相关的风险,由于治理不足而出现.
  • 该研究指出,需要适应性,部门特定的治理策略,以应对生成性AI的独特挑战.

结论:

  • 负责任地部署生成性人工智能需要采取积极主动和适应性的治理方法.
  • 拟议的五个阶段生命周期框架 (设计,实施,监测,合规,反) 提供了一个道德和安全的人工智能应用的方案.
  • 实施特定部门的适应性治理对于降低风险和确保AI在关键基础设施中的安全应用至关重要.