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Learn how to implement dependency injection patterns for on-device AI systems in this conference talk that addresses critical engineering challenges in consumer electronics applications. Explore solutions to API fragmentation caused by diverse hardware accelerators and proprietary ML frameworks, discover resource optimization techniques for devices with limited computing power, and understand strategies for model updates in embedded environments. Examine the architectural approach developed for NNStreamer, an LF AI & Data project, and see how these concepts were successfully applied to Tizen and released in commercial products in 2025. Gain insights into long-term maintenance strategies for platform sustainability and learn from real-world implementation experiences that have been upstreamed to corresponding code repositories.
