Choosing The Right Technique: Prompt Engineering vs Fine-Tuning
Data Science Central, Tuesday, January 30th, 2024
Artificial intelligence and machine learning applications have been revolutionizing many industries for the last decade, but due to generative AI models like ChatGPT, Bard, Midjourney, etc., they have become more popular and are being used by individuals and businesses that might never have previously considered using them.
Despite demonstrating tremendous potential, AI models, in reality, don't have true intelligence. Instead, AI and ML applications are systems that can identify patterns within large and complex datasets and then present these relationships to users in a meaningful way. These systems heavily depend on model optimization techniques to improve performance and drive desirable, context/ domain-specific results.
Prompt engineering and fine-tuning are two key model optimization techniques used in training GenAI models, especially large language models.