Open source versus proprietary LLMs

Open source and proprietary LLMs each have their unique strengths and limitations. Open source LLMs, accessible to everyone, can be customized to suit various requirements. They are widely employed in diverse NLP operations, from text generation to summarization, translation, and analysis. Advantages of open source LLMs over proprietary ones include enhanced flexibility, control, and affordability, as well as heightened data privacy and security.

Proprietary LLMs, on the other hand, may possess advanced features that enhance their usability and efficiency, thereby boosting their commercial appeal. Nevertheless, these models can be harder to comprehend and usually offer a narrower range of capabilities.

Specific industries and applications may restrict the use of commercial LLM services due to the sensitivity of the data involved, such as in healthcare scenarios where Personally Identifiable Information (PII) cannot be exposed due to compliance...