Inference, Guardrails, and Observability for LLMs with Jonathan Cohen
Impossible d'ajouter des articles
Désolé, nous ne sommes pas en mesure d'ajouter l'article car votre panier est déjà plein.
Veuillez réessayer plus tard
Veuillez réessayer plus tard
Échec de l’élimination de la liste d'envies.
Veuillez réessayer plus tard
Impossible de suivre le podcast
Impossible de ne plus suivre le podcast
Inference, Guardrails, and Observability for LLMs with Jonathan Cohen
-
Lu par :
-
De :
À propos de ce contenu audio
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.
Vous êtes membre Amazon Prime ?
Bénéficiez automatiquement de 2 livres audio offerts.Bonne écoute !
Aucun commentaire pour le moment
