
The promise of generative artificial intelligence (AI) has revolutionized expectations in numerous fields, from natural language processing to creative tasks like music and art generation. However, despite the growing excitement, a significant cloud hangs over the burgeoning technology: its persistent accuracy issues. While generative AI, especially large language models (LLMs), have become faster and more cost-effective, they frequently suffer from