Best practices for leveraging generative AI and LLMs

Recently, the generative AI model of a tech giant falsely attributed a $100 billion stock drop to the James Webb Space Telescope’s first image. In another instance, a DataRobot survey revealed that 62% of users experiencing AI bias suffered revenue loss and 61% lost customers. The above examples emphasize the urgency of addressing ‘prompt toxicity’ and ‘hallucination’ in generative AI and Large Language Models (LLMs) and highlight the importance of adhering to best practices that can mitigate such risks. This article will provide a comprehensive guide to adopting these practices and using generative AI and language models responsibly while safeguarding trust and reliability.