Model Selection Insights
Choosing the right model for specific requests can significantly impact both performance and costs. Opting for a larger model might seem appealing, but it can lead to exorbitant expenses and diminished efficiency. Engaging in thoughtful discussions about goals and employing basic heuristics can help organizations determine the most suitable model while managing their architecture effectively.In this clip
From this podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Building LLM-Based Applications with Azure OpenAI with Jay Emery - 657
Related Questions
How do you leverage different models in machine learning?
How do I know if I'm overengineering and doing too much upfront design in software architecture?
Is it true that when the cost of trying new technologies goes to zero, deciding what to build becomes the bottleneck, and that knowing which model output is merely plausible and which is actually good is not a commodity skill, making taste in technology a defining advantage?