Denys Linkov

What insights can we find in billions of pages of Insurance documents? Traditional Insurance models have been based on well structured data for underwriting, claims, fraud and risk. With more agentic models and the ability to utilize unstructured data, the ability to build better predictive models is improving across a number of insurance domains.

Every day we hear 100s of technical and societal claims about AI. Many of these claims and predictions come from those with significant non-public information and many technical breakthroughs are now trade-secrets veering away from an academic publishing model.

You've been given an AI mandate but don't have additional headcount, what next? Re-skilling, up-skilling and team augmentation become essential to delivering on a new mandate. In this talk we'll cover strategies to structure cross functional AI teams with domain experts, software engineers and ML engineers.

LLM accuracy is a challenging topic to address and is much more multi dimensional than a simple accuracy score. In this talk we’ll dive deeper into how to measure LLM related metrics, going through examples, case studies and techniques beyond just a single accuracy and score.