The Importance of Context-Sensitive Benchmarks
As artificial intelligence (AI) continues to evolve, the need for a new evaluation framework has become increasingly evident. Current benchmarks fail to account for the diverse environments in which AI technologies are deployed. Without robust and context-sensitive standards, we risk importing flawed models from global tech giants. These models may not perform well in local scenarios where they were never intended to be used.
This lack of tailored evaluation can lead to serious consequences. Organizations might find themselves relying on AI solutions that do not meet their specific needs. As we integrate AI deeper into various sectors, the demand for reliable and relevant benchmarks becomes crucial. By establishing a new report card for AI, we can ensure better performance and more accurate results across different applications.
