
Inference, Guardrails, and Observability for LLMs with Jonathan Cohen
Failed to add items
Sorry, we are unable to add the item because your shopping cart is already at capacity.
Add to basket failed.
Please try again later
Add to Wish List failed.
Please try again later
Remove from Wish List failed.
Please try again later
Follow podcast failed
Unfollow podcast failed
-
Narrated by:
-
By:
About this listen
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.
activate_mytile_page_redirect_t1
What listeners say about Inference, Guardrails, and Observability for LLMs with Jonathan Cohen
Average Customer RatingsReviews - Please select the tabs below to change the source of reviews.
In the spirit of reconciliation, Audible acknowledges the Traditional Custodians of country throughout Australia and their connections to land, sea and community. We pay our respect to their elders past and present and extend that respect to all Aboriginal and Torres Strait Islander peoples today.