LLM Safety Review: Benchmarks & Analysis
Find out what happened when we tested the responses of six leading LLMs, in 7 languages, to over 20,000 prompts related to child exploitation, hate speech, suicide and self-harm, and misinformation.
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LLM Safety Review: Benchmarks & Analysis
Overview
As more and more applications implement Generative AI, a clear understanding of foundation models' safety risks becomes imperative. During this webinar, we will review the outcomes of Alice's LLM safety benchmarking report, which evaluated whether gaps exist in the basic safety of GenAI apps and LLM providers. From child exploitation to misinformation, hate speech to self-harm, we will discuss harmful model outputs, the ways bad actors can abuse LLMs, and the risks to those applications that rely on them. Join us to learn about how we evaluated LLM safety, and what risks you should consider as you implement these models into your applications.
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.