⚡ 本页包含 AI 生成的分析内容，仅供参考
本文展望了计算技术的未来，提出比特（经典计算）、神经元（人工智能）和量子比特（量子计算）三种范式融合的趋势。文章回顾了基于比特和摩尔定律的数字化进程，以及近期AI系统在窄分类任务中实现的超人精度，并探讨了从狭义AI向更通用智能的演进。
Abstract The laptops, cell phones, and Internet applications commonplace in our daily lives are all rooted in the idea of zeros and ones – in bits. This foundational element originated from the combination of mathematics and Claude Shannon’s Theory of Information. Coupled with the 50-year legacy of Moore’s Law, the bit has propelled the digitization of our world. In recent years, artificial intelligence systems, merging neuron-inspired biology with information, have achieved superhuman accuracy in a range of narrow classification tasks by learning from labelled data. Advancing from Narrow AI to Broad AI will encompass the unification of learning and reasoning through neurosymbolic systems, resulting in a form of AI which will perform multiple tasks, operate across multiple domains, and learn from small quantities of multi-modal input data. Finally, the union of physics and information led to the emergence of Quantum
Dario Gil, William M. J. Green
IBM Thomas J. Watson Research Center, Yorktown Heights, NY