What is the future of model versioning in AI?
The future of model versioning in AI is likely to focus on automation, better tracking, and integration with CI/CD pipelines.
How will automation change the way we manage model versions?
Automation will streamline the process, allowing for real-time updates and easier rollback to previous versions when needed.
What tools are emerging for model versioning?
Tools like DVC, MLflow, and Weights & Biases are gaining popularity for their robust versioning capabilities.
Will model versioning become standardized?
It's possible! As the field matures, we may see more standardized practices and protocols for model versioning.
What challenges do we face in model versioning?
Challenges include managing dependencies, ensuring reproducibility, and handling large datasets efficiently.
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