Artificial intelligence (AI) stands out as a transformational technology of the digital age. Its practical applications are growing very rapidly. One of the chief reasons AI applications are attaining prominence, is in its design to learn continuously, from real-world use and experience, and its capability to improve its performance. It is no wonder that the applications of AI span from complex high-technology equipment manufacturing to personalized exclusive recommendations to end-users. Many deployments of AI software, given its continuous learning need, require computation platforms that are resource intense, and have sustained connectivity and perpetual power through central electrical grid. In order to harvest the benefits of AI revolution to all of humanity, traditional AI software development paradigms must be upgraded to function effectively in environments that have resource constraints, small form factor computational devices with limited power, devices with intermittent or no connectivity and/or powered by non-perpetual source or battery powered. The aim this book is to prepare current and future software engineering teams with the skills and tools to fully utilize AI capabilities in resource-constrained devices. The book introduces essential AI concepts from the perspectives of full-scale software development with emphasis on creating niche Blue Ocean small form factored computational environment products. It also: Outlines Artificial Intelligence Software Architecture & Cloud Architecture with emphasis to Edge Computing. Provides comprehensive comparison and applicability of AI algorithms in constrained environments: Supervised, Unsupervised, and Reinforcement Emphasis real-time embedded storages for AI applications, specific to constrained environments Develops AI Driver Software code with real-time deep learning small footprint frameworks such as tensor flow, python, C, Android and iOS Swift. Provides exclusive AI field deployments that operate in remote & non-connected environments Explains AI solution development from a Product management perspective The book details several AI reference architectures with emphasis on democratizing Artificial Intelligence to environments that operate under compute & network connectivity issues.