Michelle Yi

The increasing deployment of generative AI models in production environments introduces new security challenges, particularly in the realm of adversarial attacks.

This 90 minute workshop explores how to leverage the open-source ecosystem and cutting-edge technologies in causal machine learning to enhance decision-making processes.

With easier access to expert knowledge, we are in the midst of a significant shift in the technical education and publishing landscapes. Do these advancements propel us toward educational bliss or do they pose unprecedented threats to industry and academia?

The adoption and application of Large Language Models (LLMs) such as Llama 2, Falcon 40B, GPT-4, etc. in building generative AI applications is an exciting and emerging domain.

In a world obsessed with making predictions and generative AI, we often overlook the crucial task of making sense of these predictions and understanding results.

The world is full of poorly tuned queries and badly designed data models that don’t accurately reflect the business. This hairball leads to excessive hardware and operational costs – not to mention a frustrating degree of customization required for each and every application.

Creating apps to model complex and dynamic environments is challenging and often implies a longtail maintenance burden. In this session, we’ll look at how a relational approach to graphs can tackle one of the most complex situations to model: disasters in cities around the world.The UN Office for Information Technology has partnered with Relational.AI to support the analysis of ongoing stresses an