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相关概念视频

Regulation of Metabolism01:19

Regulation of Metabolism

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Cellular needs and conditions vary from cell to cell and change within individual cells over time. For example, the required enzymes and energetic demands of stomach cells are different from those of fat storage cells, skin cells, blood cells, and nerve cells. Furthermore, a digestive cell works much harder to process and break down nutrients during the time that closely follows a meal compared with many hours after a meal. As these cellular demands and conditions vary, so do the amounts and...
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Drug control governance involves the oversight and regulation of pharmaceuticals to ensure their safety and efficacy while preventing illegal drug use and trafficking. Regulatory bodies, including the US Food and Drug Administration (FDA) and the European Union's European Medicines Agency (EMA), play a central role in this process. These agencies evaluate the safety and efficacy of drugs before they can be marketed. They fund clinical trials and assess the benefits and risks associated with...
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Indirect-acting cholinergic agonists are agents that interact with the acetylcholinesterase enzyme in the synaptic cleft, preventing the breakdown of acetylcholine into choline and acetate. Consequently, the concentration of acetylcholine in the synaptic cleft increases. These agonists can be classified into reversible and irreversible inhibitors based on their duration of action.
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The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the...
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Synthetic Biology02:55

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Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses
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监管先进的人工制剂

Michael K Cohen1,2, Noam Kolt3,4, Yoshua Bengio5,6

  • 1University of California, Berkeley, CA, USA.

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PubMed
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此摘要是机器生成的。

需要新的治理框架来管理可能带来安全风险且无法测试的人工智能系统. 这项研究突显了对可适应人工智能治理的必要性, 以确保公共安全.

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科学领域:

  • 计算机科学
  • 人工智能道德
  • 公共政策

背景情况:

  • 人工智能 (AI) 的快速发展带来了前所未有的社会利益和风险.
  • 目前的人工智能治理框架主要依赖于测试和验证,这对于复杂或不可预测的人工智能系统来说可能不足.
  • 确保人工智能的安全性和可靠性至关重要,因为它将越来越多地融入关键基础设施和决策过程.

研究的目的:

  • 探索无法安全测试的人工智能系统带来的挑战.
  • 提出必要的治理框架调整以应对这些挑战.
  • 确保人工智能技术的负责任开发和部署.

主要方法:

  • 对现有的人工智能治理模型和安全测试方法的文献审查.
  • 对抗传统安全评估的理论AI系统的分析.
  • 为无法测试的人工智能开发概念治理原则.

主要成果:

  • 特定的AI特征 (例如,新出现的行为,黑盒性质) 排除了安全测试.
  • 建议从纯粹的经验安全验证转向更强有力的基于原则的治理方法.
  • 强调需要持续监测和适应性监管战略.

结论:

  • 现有的人工智能治理框架对于无法安全测试的系统是不够的.
  • 未来的治理必须包括积极的风险管理和对人工智能的适应性监督.
  • 解决未经测试的AI挑战对于保持公众对AI部署的信任和安全至关重要.