Part 10/11:
Choosing the right tool depends on your goal. If you want a model that performs specific tasks, fine-tuning may help—yet it remains an expensive and complex process.
For knowledge management and QA, semantic search is the superior approach, combining speed, scalability, and accuracy.
Conclusion
David Shapiro’s insights highlight that fine-tuning and semantic search serve fundamentally different purposes. Fine-tuning is best for teaching models to recognize patterns or perform new tasks, but it is not a substitute for a robust retrieval system when it comes to storing, recalling, and verifying factual information.