Alice x NVIDIA Webinar: Scaling AI Safely, Securing the Next Generation of AI Agents
Join Alice and Nvidia for this exclusive Webinar - Discover how industry leaders are securing their AI deployments.
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Alice x NVIDIA Webinar: Scaling AI Safely, Securing the Next Generation of AI Agents
Overview
More and more businesses are starting to deploy agentic AI. From customer support chatbots and virtual assistants to intelligent multimodal agents, these autonomous and powerful AI systems are transforming industries. But scaling them safely presents unique challenges.
Alice and NVIDIA have partnered to help enterprises navigate these challenges with confidence. Join this live webinar to learn how to build, deploy, and manage secure AI agents without compromising innovation or speed.
What You'll Learn:
- How to deploy chatbots securely with integrated, real-time guardrails.
- Techniques for continuous risk mitigation through automated red teaming.
- Strategies to ensure compliance and proactively prevent harmful content.
- Proactive safety-by-design strategies and best practices for multimodal safety across text, image, and audio inputs.
- Industry-specific insights and practical use cases.
Agenda Highlights:
- Deep dive into NVIDIA's AI Factory and Safety Flywheel integration with ActiveFence.
- Live demonstration of guardrails preventing real-time risks.
- Industry-specific use cases and future roadmap.
- Interactive Q&A session.
Watch On-Demand Today.
Meet our speakers
What’s New from Alice
Securing Agentic AI: The OWASP Approach
In this episode, Mo Sadek is joined by Steve Wilson (Chief AI and Product Officer at Exabeam, founder and co-chair of the OWASP GenAI Security Project) to explore how OWASP is shaping practical guidance for agentic AI security. They dig into prompt injection, guardrails, red teaming, and what responsible adoption can look like inside real organizations.
Distilling LLMs into Efficient Transformers for Real-World AI
This technical webinar explores how we distilled the world knowledge of a large language model into a compact, high-performing transformer—balancing safety, latency, and scale. Learn how we combine LLM-based annotations and weight distillation to power real-world AI safety.