How to Choose the Right AI Foundation Model?

After reading this book, you will learn:

Importance of AI Model Selection

Organizations need to understand the nuances of AI model selection to achieve desired outcomes effectively. ​ Choosing the right model is crucial as it impacts various business aspects, including finance, strategy, and legal considerations. ​

Different outcomes require tailored approaches in data preparation and model selection.

Risks include biases from training data and potential legal issues from faulty outcomes. ​
An evaluation framework helps accommodate diverse needs of AI users, from data scientists to decision-makers. ​

Evaluating Model Size, Performance, and Risks

Assessing model size, performance, and associated risks is essential for effective AI implementation. ​ The trade-offs between model size and performance can significantly influence the outcomes. ​

Testing and Choosing the Right Model

Testing various models and selecting the one that delivers the best value is a key step in the model selection process. ​ This involves evaluating performance metrics and refining choices based on specific needs. ​

Identifying Clear Use Cases for AI

Clearly articulating use cases is vital for selecting the appropriate AI model. ​ Understanding specific business needs and crafting precise prompts can lead to better model alignment. ​