As with past technology adoption journeys, initial experimentation costs eventually shift to a focus on ROI. In a recent post on X, Andrew Ng extensively discussed GenAI model pricing reductions. This is great news, since GenAI models are crucial for powering the latest generation of AI applications. However, model swapping is also emerging as both an innovation enabler, and a cost saving strategy, for deploying these applications. Even if you’ve already standardized on a specific model for your applications with reasonable costs, you might want to explore the added benefits of a multiple model approach facilitated by Kubernetes.
A Multiple Model Approach to GenAI
A multiple model operating approach enables developers to use the most up-to-date GenAI models throughout the lifecycle of an application. By operating in a continuous upgrade approach for GenAI models, developers can harness the specific strengths of each model as they shift over time. In addition, the introduction of specialized, or purpose-built models, enables applications to be tested and refined for optimal accuracy, performance and cost.