Computers are grounded in Boolean logic, via transistors that implement simple logical functions: AND, NAND, OR, and NOR gates. Much of the confidence embodied in the quote from this first era of AI lay in the formal and expressive power of logic and mathematics. I will argue that artificial general intelligence-able to range across widely differing tasks and contexts-is unlikely to be developed, or emerge, any time soon. More generally, our AI systems remain singular task-achieving architectures, often termed narrow AI. One consequence of recent AI accomplishments is a renaissance of interest around the ethics of such systems. At the same time, there is growing unease around whether the behavior of these systems can be rendered transparent, explainable, unbiased, and accountable. The exponential increases in computing power, open-source software, available data, and embedded services have been crucial to this success. ![]() In particular, modern machine learning methods have enabled a series of AI systems to achieve superhuman performance. Reviewing the history and current state of the art reveals a broad repertoire of methods and techniques developed by AI researchers. ![]() Recent achievements have seen renewed claims for the transformative and disruptive effects of AI. Artificial intelligence has a decades-long history that exhibits alternating enthusiasm and disillusionment for the field's scientific insights, technical accomplishments, and socioeconomic impact.
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