Many organizations struggle to create a well-orchestrated AI infrastructure, using separate and disconnected platforms for data processing, model training, and inference, which slows down development and increases costs. There’s a clear need for a unified system that can handle all aspects of AI development and deployment, regardless of the size of data or models. Join our breakout session to see how our comprehensive solution simplifies the development and deployment of large language models in production. Learn how to streamline your AI operations by implementing an end-to-end ML lifecycle on your custom data, including - automated LLM fine-tuning, LLM evaluation & LLM serving and LoRA deployments
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Venkata Jagannath
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Senior ML Engineer, Astronomer
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