We will talk with you about red teaming, and evaluation of safety and biases of LLMs. We're investing in this area and want to share our approach with model-builders, app-builders and industry regulators. AI technology is moving past the Proof-of-Concept stage, and today we better understand its power and limitations. From regulators and research institutes to enterprises and startups, all our clients are paying closer attention to pre-release and in-production model evaluation. While there is a lot of great research today, many gaps still exist: some focus on the extremely basic topics, others explore about futuristic risks. We want to walk you through our risk-based methodology for evaluating safety and biases that is in the middle of these extremes. Here's what you can expect from this session: - A bit of theory: why it matters, safety methods overview, and safety evaluation techniques. - A DIY guide: how to create your own safety policy evaluation, assess fairness & biases, and when and how to use red-teaming. - What to assess: major risk categories, user and model intents and scenarios.