• Inference, Guardrails, and Observability for LLMs with Jonathan Cohen

  • 2024/11/09
  • 再生時間： 53 分
  • ポッドキャスト

Inference, Guardrails, and Observability for LLMs with Jonathan Cohen

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  • In this episode of AI Explained, we are joined by Jonathan Cohen, VP of Applied Research at NVIDIA.

    We will explore the intricacies of NVIDIA's NeMo platform and its components like NeMo Guardrails and NIMS. Jonathan explains how these tools help in deploying and managing AI models with a focus on observability, security, and efficiency. They also explore topics such as the evolving role of AI agents, the importance of guardrails in maintaining responsible AI, and real-world examples of successful AI deployments in enterprises like Amdocs. Listeners will gain insights into NVIDIA's AI strategy and the practical aspects of deploying large language models in various industries.
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あらすじ・解説

In this episode of AI Explained, we are joined by Jonathan Cohen, VP of Applied Research at NVIDIA.

We will explore the intricacies of NVIDIA's NeMo platform and its components like NeMo Guardrails and NIMS. Jonathan explains how these tools help in deploying and managing AI models with a focus on observability, security, and efficiency. They also explore topics such as the evolving role of AI agents, the importance of guardrails in maintaining responsible AI, and real-world examples of successful AI deployments in enterprises like Amdocs. Listeners will gain insights into NVIDIA's AI strategy and the practical aspects of deploying large language models in various industries.
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