In the rapidly evolving AI landscape, organizations must prioritize portability in their AI projects to adapt swiftly to advancements and mitigate vendor lock-in.
To future-proof AI initiatives, adopting a model-agnostic approach is essential. This flexibility allows users to leverage the latest model advancements effectively.
Flexible training pipelines and standardized data formats are critical to ensure that AI applications can seamlessly integrate with multiple models without incurring high costs.
At the AI Builders Summit, my talk will explore effective ways to evaluate multiple models, deploy them efficiently, and optimize their performance for various projects.
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