Human-level AI will have significant impacts on human society. However, estimates for the realization time are debatable. To arrive at human-level AI, artificial general intelligence (AGI), as opposed to AI systems that are specialized for a specific task, was set as a technically meaningful long-term goal. But now, propelled by advances in deep learning, that achievement is getting much closer. Considering the recent technological developments, it would be meaningful to discuss the completion date of human-level AI through the "comprehensive technology map approach," wherein we map human-level capabilities at a reasonable granularity, identify the current range of technology, and discuss the technical challenges in traversing unexplored areas and predict when all of them will be overcome. This paper presents a new argumentative option to view the ontological sextet, which encompasses entities in a way that is consistent with our everyday intuition and scientific practice, as a comprehensive technological map. Because most of the modeling of the world, in terms of how to interpret it, by an intelligent subject is the recognition of distal entities and the prediction of their temporal evolution, being able to handle all distal entities is a reasonable goal. Based on the findings of philosophy and engineering cognitive technology, we predict that in the relatively near future, AI will be able to recognize various entities to the same degree as humans.
翻译:人类层面的AI将对人类社会产生重大影响。然而,对实现时间的估计是值得商榷的。 人类层面的AI, 人造一般智能(AGI),相对于专门从事特定任务的AI系统(AGI),人类层面的人工一般智能(AGI),被确定为技术上有意义的长期目标。但如今,在深层次学习进步的推动下,这一成就正在变得越来越接近。考虑到最近的技术发展,通过“综合技术地图”来讨论人类层面AI的完成日期是有意义的。 通过“综合技术地图”,我们从合理的粒子上绘制人类层面的能力图,确定当前的技术范围,并讨论在未探索领域探索的技术挑战,并预测所有这些领域将何时克服。本文件提出了一个新的论证选项,以观察肿瘤性研究,它包含与我们日常直觉和科学实践相一致的实体,作为全面的技术图。 如何解释世界的模型,通过一个明智的课题,即识别分化实体及其时间进化的预测,以及预测其时间进化范围,并预测所有这些未探索的领域将会克服。 本文提出了一个新的论证选项,即以与人类层面性性别学学学学的模型一样,我们能够对各种技术进行相对的预测。