Abstract
Artificial intelligence and machine learning have significantly advanced in the last few years and are expected to continue a trajectory of increased adoption and impact. This growth is driven by a number of technological and social developments over the past few years. According to Gartner, a technology research and consulting firm, the drivers for growth in AI are (1) the increasing volume and availability of big data and the developments in parallel processing systems that can cost-effectively store and process data at massive scale; (2) the advancements in computer hardware, particularly the emergence of powerful graphics processing units (GPUs) for complex computations; (3) the development of new machine learning (ML) techniques; (4) the emergence of cloud computing, which enables faster experimentation with and operationalization of AI with lower complexity; and (5) the vibrant open-source ecosystem, which has enabled many deep learning frameworks and resulted in an explosion of startups [1].
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El Morr, C., Jammal, M., Ali-Hassan, H., El-Hallak, W. (2022). Future Directions and Ethical Considerations. In: Machine Learning for Practical Decision Making. International Series in Operations Research & Management Science, vol 334. Springer, Cham. https://doi.org/10.1007/978-3-031-16990-8_16
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