The AI tech stack is evolving at lightning speed, making it critical for teams to adopt solutions that balance innovation with scalability. Embedding models and vector databases are at the core of AI-native applications, enabling powerful search, recommendation, and personalization capabilities. Yet, navigating the complexity of self-hosting, open-source tools, and integration challenges can slow progress. This webinar explores practical strategies to simplify AI development while staying ahead of the curve in 2025.
What You’ll Learn:
How to select the right embedding model for your specific use case.
Tips for optimizing both performance and cost.
Key strategies for accelerating AI-native development in the cloud.
How to leverage open-source tools for greater flexibility and control.
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