Neural Architecture Search defines efficient search spaces for tailoring architectures in tasks like image classification and NLP..Differentiable architecture search optimizes NAS processes, leveraging gradients to improve speed and accessibility for broader AI applications..Weight-sharing techniques reduce training times, enhancing NAS efficiency by reusing learned representations across multiple architectures..Benchmarks like NAS Bench-101 standardize comparisons, advancing research in neural network optimization across datasets and tasks..NAS expands into healthcare, vision, and NLP, offering robust, efficient architectures for diverse real-world challenges..Read More Stories