This talk presents the SODA (Software Defined Accelerators) framework, an open-source modular, multi-level, no-human-in-the-loop, hardware compiler that enables end-to-end generation of specialized accelerators from high-level data science frameworks. SODA is composed of SODA-Opt, a high-level frontend developed in MLIR that interfaces with domain-specific programming environments and allows performing system level design, and Bambu, a state-of-the-art high-level synthesis (HLS) engine that can target different device technologies. The framework implements design space exploration as compiler optimization passes. We show how the modular, yet tight, integration of the high-level optimizer and lower-level HLS tools enables the generation of accelerators optimized for the computational patterns of novel "converged" applications. We then discuss some of the research opportunities that such an open-source framework allows.