As I’ve talked to numerous CEO’s of Saas companies I have noticed a common and unsurprising trend. Many of them are excited about the potential of Generative AI to transform their business, both through innovation in their product roadmap and potential productivity gains provided to their team’s and workforce.
Yet just as common as the excitement for GenAI is an emotion many soon run into – perplexity. It’s easy for a business leader to feel inspired or awestruck at the creation of Dall-E3 or Stability AI of a cat riding a horse in outer space. But it’s another thing to define clear cut business use cases for a powerful new platform.
In this article I’ll break down what I have noticed as common and practical use cases for GenAi that can drive meaningful business value and won’t break the bank to implement.
Before we dive into these use cases however, it’s important to understand 3 key phases to developing and implementing a foundational model, or FM.
- Pretraining
- Fine-tuning
- Prompt engineering
Logan Coffman 