Four key considerations for business executives
Harnessing the potential of Generative AI (GenAI) to create user applications that drive business value may appear daunting, yet it doesn’t need to be. With the GenAI field advancing swiftly and offering a plethora of options, understanding the following four fundamental areas can provide clarity for business leaders:
- User Interface (UI) Design for Prompt Interaction – GenAI applications typically rely on user prompts to generate responses. A well-designed UI, effective prompt engineering, rigorous testing, and user training are crucial aspects. Tailoring the UI to enable users to establish “context” for GenAI responses is paramount.
- Implementing Prompt and Response Filtering – Establishing controls to govern how GenAI models respond to prompts and filtering out undesirable content is essential. This ensures that the generated responses align with organizational standards and objectives. The focus should be on providing guardrails in case the GenAI models deviate from safety standards.
- Selecting a Baseline GenAI Model – Choosing the right baseline GenAI model is pivotal. These pre-trained deep learning models serve as the foundation and offer a starting point for application development. Careful consideration of factors such as application type, cost, and computational requirements is imperative when selecting from a range of commercial and open-source options.
- Fine-Tuning for Optimal Performance – Enhancing the performance of baseline models through fine-tuning is indispensable. Fine-tuning involves leveraging additional data to adapt the baseline model to specific use cases, such as generating journalistic essays, customer support, legal documents, etc. Organizations should deliberate on how they intend to fine-tune GenAI models to align with their unique requirements.
While building GenAI applications entails inherent complexity, focusing on these considerations provides a valuable blueprint for developing high-quality user applications driven by Generative AI technology.
