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Futures of artificial intelligence through technology readiness levels

机译:通过技术准备水平的人工智能期货

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Artificial Intelligence (AI) offers the potential to transform our lives in radical ways. However, the main unanswered questions about this foreseen transformation are its depth, breadth and timelines. To answer them, not only do we lack the tools to determine what achievements will be attained in the near future, but we even ignore what various technologies in present-day AI are capable of. Many so-called breakthroughs in AI are associated with highly-cited research papers or good performance in some particular benchmarks. However, research breakthroughs do not directly translate into a technology that is ready to use in real-world environments. In this paper, we present a novel exemplar-based methodology to categorise and assess several AI technologies, by mapping them onto Technology Readiness Levels (TRL) (representing their depth in maturity and availability). We first interpret the nine TRLs in the context of AI, and identify several categories in AI to which they can be assigned. We then introduce a generality dimension, which represents increasing layers of breadth of the technology. These two dimensions lead to the new readiness-vs-generality charts, which show that higher TRLs are achievable for low-generality technologies, focusing on narrow or specific abilities, while high TRLs are still out of reach for more general capabilities. We include numerous examples of AI technologies in a variety of fields, and show their readiness-vs-generality charts, serving as exemplars. Finally, we show how the timelines of several AI technology exemplars at different generality layers can help forecast some short-term and mid-term trends for AI.
机译:人工智能(AI)提供了以激进方式改变生活的潜力。然而,关于这种预见的主要问题是它的深度,广度和时间表。为了回答它们,我们不仅缺乏工具,可以确定在不久的将来将获得什么成就,但我们甚至忽略了当天AI中的各种技术的能力。在AI中许多所谓的突破与一些特定的基准中的高度引用的研究论文或良好的性能相关联。然而,研究突破不会直接转化为准备在现实世界环境中使用的技术。在本文中,我们通过将它们映射到技术准备水平(TRL)(表示成熟度和可用性中的深度)来介绍基于一个基于一个基于AI技术的方法。我们首先在AI的上下文中解释九个TRL,并识别可以分配它们的AI中的几个类别。然后,我们介绍了一般性维度,这代表了技术的增加层。这两个维度导致新的准备就绪 - 与一般性图表,这表明,对于低通用技术,可实现更高的TRL,专注于狭窄或特定的能力,而高TRL仍然无法达到更多通用能力。我们包括各种字段中的众多AI技术的示例,并显示其准备就是作为示例的vs-permentality图表。最后,我们展示了不同一般性层的几个AI技术示范的时间表如何有助于预测AI的一些短期和中期趋势。

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