Building Secure and Trustworthy LLMs Using NVIDIA Guardrails / with Nayan Saxena.

Format:

Video

Author/Creator:

Saxena, Nayan, speaker.

Contributor:

linkedin.com (Firm)

Language:

English

Genre:

Instructional films.

Educational films.

Physical Description:

1 online resource

Place of Publication:

Carpenteria, CA : linkedin.com, 2024.

System Details:

Latest version of the following browsers: Chrome, Safari, Firefox, or Internet Explorer. Adobe Flash Player Plugin. JavaScript and cookies must be enabled. A broadband Internet connection.

digital

Summary:

Take a deep dive into the world of language large models (LLMs), and learn how to implement robust guardrails for secure, ethical AI use.

Guardrails are essential components of large language models (LLMs) that can help to safeguard against misuse, define conversational standards, and enhance public trust in AI technologies. In this course, instructor Nayan Saxena explores the importance of ethical AI deployment to understand how NVIDIA NeMo Guardrails enforces LLM safety and integrity. Learn how to construct conversational guidelines using Colang, leverage advanced functionalities to craft dynamic LLM interactions, augment LLM capabilities with custom actions, and elevate response quality and contextual accuracy with retrieval-augmented generation (RAG). By witnessing guardrails in action and analyzing real-world case studies, you'll also acquire skills and best practices for implementing secure, user-centric AI systems. This course is ideal for AI practitioners, developers, and ethical technology advocates seeking to advance their knowledge in LLM safety, ethics, and application design for responsible AI.

Participant:

Presenter: Nayan Saxena

Notes:

9/13/202412:00:00AM

Access Restriction:

Restricted for use by site license.