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University of Notre Dame
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AI-assisted IDEs are fundamentally changing how developers work, shifting from upfront task specification to iterative refinement, and from direct code engagement to delegating diagnosis and validation to the AI.
Algorithm-hardware co-design could revolutionize medical technology, but realizing its potential requires a fundamental shift in how these systems are conceived, designed, validated, and translated into practice.
Even tiny hardware imperfections in compute-in-memory accelerators can trigger catastrophic failures in neural networks, demanding new co-design strategies.
