In this session, we will discuss the impact of regulation on AI development and the future landscape of AI and data privacy with leading organizations using Federated Learning technology.
We will learn the technical aspects of how Federated Learning is being applied in healthcare as well as in the industrial world.
Instant decision-making and processing is critical in industries, such as autonomous vehicles, industrial automation, smart grids where the slightest delay can have significant consequences.
In this panel we will cover the infrastructure requirements for real-time AI and deployment tools and platforms that are optimized for edge AI.
Model compression techniques and the use of hardware accelerators, such as GPUs and specialized AI chips, pose new distributed computing scenarios for data-intensive applications.
In this round table, we will discuss scalability challenges for data-intensive deployments and the techniques used for optimizing Machine Learning Operations.
Deploying robust, and secure ML systems for uninterrupted business operations is key in industries such as energy, oil and gas, water utility and critical infrastructures where independence from connectivity, suppliers, and changing conditions is paramount to business continuity.
In this session, we will share best practices in safeguarding ML deployments in the Edge.