AI Benchmark

AI benchmarking aims to objectively evaluate the performance and efficiency of artificial intelligence models, guiding development and deployment. Current research focuses on creating more comprehensive and realistic benchmarks that address limitations of existing methods, including the development of benchmarks tailored to specific application domains (like scientific computing and healthcare) and the exploration of energy-efficient model architectures such as spiking neural networks. Improved benchmarking is crucial for fostering responsible AI development, enabling better comparisons between models, and ultimately accelerating progress in various scientific fields and practical applications.