Artificial intelligence (AI) has immense potential spanning research and industry. AI applications abound and are expanding rapidly, yet the methods, performance, and understanding of AI are in their infancy. Researchers face vexing issues such as how to improve performance, transferability, reliability, comprehensibility, and how better to train AI models with only limited data. Future progress depends on advances in hardware accelerators, software frameworks, system and architectures, and creating cross-cutting expertise between scientific and AI domains. Open Compass is an exploratory research project to conduct academic pilot studies on an advanced engineering testbed for artificial intelligence, the Compass Lab, culminating in the development and publication of best practices for the benefit of the broad scientific community. Open Compass includes the development of an ontology to describe the complex range of existing and emerging AI hardware technologies and the identification of benchmark problems that represent different challenges in training deep learning models. These benchmarks are then used to execute experiments in alternative advanced hardware solution architectures. Here we present the methodology of Open Compass and some preliminary results on analyzing the effects of different GPU types, memory, and topologies for popular deep learning models applicable to image processing.
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How Artificial Intelligence and Deep Learning are Changing the Healthcare Industry
This research paper will discuss the various technological innovations that have been developed within the past, are being developed in the present and will be developed in the future to bring progressive change within the healthcare industry. In particular, the way artificial intelligence and deep learning has brought about new methods for making task more efficient, less time consuming, and possibly more accurate. This study will discuss the different positive and negative effects of these technological methods to best see how artificial intelligence (AI) and deep learning is impacting the health industry in all areas. With supportive interviews from medical professionals, data scientist, and machine learning researchers, the analysis of real-world experiences and scenarios will provide more insight to what is beneficial or ineffective. The study utilizes extensive literary works to examine in detail the current AI and deep learning new approach to medicine, the risk and ethical concerns, the technological challenges from determining the best algorithms, and myths versus reality surrounded by this subject.
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- Award ID(s):
- 1458729
- PAR ID:
- 10301438
- Date Published:
- Journal Name:
- The ADMI 2021 Symposium
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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