Effecient LLM Deployment: A Unified Approach with Ray, VLMM, and Kubernetes - L (Xiaoxuan) Liu

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Effecient LLM Deployment: A Unified Approach with Ray, VLMM, and Kubernetes - L (Xiaoxuan) Liu, Anyscale

With the groundbreaking release of ChatGPT, large language models (LLMs) have taken the world by storm: they have enabled new applications, have exacerbated GPU shortage, and raised new questions about their answers’ veracity. This talk delves into an AI stack, encompassing cloud-native orchestration, distributed computing, and advanced LLMOps. Key topics include: - Kubernetes: The foundational technology that seamlessly manages AI workloads across diverse cloud environments. - Ray: The versatile, open-source framework that streamlines the development and scaling of distributed applications. - vLLM: The cutting-edge, high-performance, and memory-efficient inference and serving engine designed specifically for large language models. Attendees will gain insights into the architecture and integration of these powerful tools, driving innovation and efficiency in the deployment of AI solutions.
  1. CNCF [Cloud Native Computing Foundation]
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