The field of artificial intelligence has seen explosive growth and exponential success. The last phase of development showcased deep learnings ability to solve a variety of difficult problems across a multitude of domains. Many of these networks met and exceeded human benchmarks by becoming experts in the domains in which they are trained. Though the successes of artificial intelligence have begun to overshadow its failures, there is still much that separates current artificial intelligence tools from becoming the exceptional general learners that humans are. In this paper, we identify the ten commandments upon which human intelligence is systematically and hierarchically built. We believe these commandments work collectively to serve as the essential ingredients that lead to the emergence of higher-order cognition and intelligence. This paper discusses a computational framework that could house these ten commandments and suggests new architectural modifications that could lead to the development of smarter, more explainable, and generalizable artificial systems inspired by a neuromorphic approach.
翻译:人工智能领域出现了爆炸性增长和指数性的成功。 发展的最后阶段展示了解决众多领域各种难题的深层次学习能力。 许多这些网络通过成为培训领域的专家而达到并超过了人的基准。 尽管人工智能的成功开始掩盖其失败,但仍有许多因素可以将当前人工智能工具与人类的特异普通学习者区分开来。 在本文件中,我们确定了人类智能系统化和分级构建的十诫。 我们相信这些命令共同发挥作用,成为导致更高秩序认知和情报出现的基本元素。 本文讨论了可以容纳这十诫的计算框架,并提出新的建筑修改建议,这些修改可以导致发展由神经形态学方法启发的更聪明、更可解释和可普及的人工系统。