Recognition of All Categories of Entities by AI
Hiroshi Yamakawa, Yutaka Matsuo

TL;DR
This paper discusses the potential for AI to achieve human-level recognition of all entity categories by mapping technological progress and challenges, suggesting near-future capabilities based on philosophical and engineering insights.
Contribution
It introduces a comprehensive technological map approach using the ontological sextet to analyze AI's ability to recognize all entity types, linking philosophy and engineering.
Findings
AI will likely recognize all entity categories at human level soon
The ontological sextet provides a framework for comprehensive entity recognition
Technological challenges are identified and mapped for future progress
Abstract
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…
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Taxonomy
TopicsSpace Science and Extraterrestrial Life · Cognitive Science and Education Research · Scientific Research and Philosophical Inquiry
