Tag: Large Language Models

Self-construction benchmarks are essential to evaluate the capabilities of Large Language Models (LLM). We use agentive artificial intelligence to have LLM generate and evaluate practical exams in Finance, Business Operations, Management, Computing, and Mathematics. Although leading models achieve median scores of 65-79%, they show weaknesses in data manipulation and financial calculations. LLM-generated benchmarks can offer a cost-effective, scalable, and updatable way to measure the job capabilities of artificial intelligence.