It is widely recognized that commonsense knowledge is essential for intelligent behavior. Unfortunately, commonsense knowledge is notoriously difficult to acquire and formalize. Consequently, AI systems often lack commonsense knowledge and fail to behave intelligently in many everyday situations.
There has been significant recent progress in harnessing AI to acquire commonsense knowledge. A central challenge in this endeavor is how to efficiently acquire the vast amount of commonsense knowledge that is required to enable intelligent behavior. Recently, deep learning methods have been employed to learn commonsense knowledge from large-scale text corpora such as the Common Crawl. These methods have shown promise in learning many kinds of commonsense knowledge, including knowledge about objects, events, and social relations.
In addition to learning commonsense knowledge from text, there is also active research on learning commonsense knowledge from other sources, such as images, video, and sensor data. For example, research has shown that it is possible to learn about objects and their properties from images, and about events and their causes from video. There is also promising work on learning commonsense knowledge from sensor data, such as data from the Internet of Things.
Overall, AI has made great progress in recent years in acquiring commonsense knowledge. There is still much work to be done, however, in order to enable AI systems to behave intelligently in all sorts of everyday situations.
References:
https://www.google.com/search?q=commonsense+knowledge&oq=commonsense+knowledge&aqs=chrome..69i57j0l7.2504j0j9&client=ms-android-transsion-tecno- recreational&sourceid=chrome-mobile&ie=UTF-8
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