The present disclosure is related to framework for automatically and efficiently finding machine learning (ML) architectures that generalize well across multiple artificial intelligence (AI) and/or ML domains, AI/ML tasks, and datasets. The ML architecture search framework accepts a list of tasks and corresponding datasets as inputs, and may also include relevancy scores/weights for each item in the input. A combined performance metric is generated, where this combined performance metric quantifies the performance of the ML architecture across all the specified AI/ML domains, AI/ML tasks, and datasets. The system then performs a multi-objective ML architecture search with the combined performance metric, along with hardware-specific performance metrics as the objectives. Other embodiments may be described and/or claimed.
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