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Table Of Contents
Architecting AI Software Systems
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A principal insight in this new era of data analytics and science is that a system’s effectiveness is dependent on the quality of the data. This truism applies to the training and configuring of models, inference, the validation processes, and the production data. This has led to the emergence of a new engineering sub-specialty: the data engineer.
The data engineer must deal with the volume, velocity, variety, and provenance of the total data ecosystem. The field of data engineering is still in its early stages. These activities are now recognized as an engineering sub-specialty rather than “just data processing.” When one engineers a system, the concepts and processes of architecture come to the fore. The data engineering efforts require the scoping of the data volumes, processing needs, storage capacity, and networking infrastructure. These analyses impact the planning of required hardware and software tooling.
As part of the architecting...
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