Mhamed Kottilungal

In this session I will start with identifying the current problems in Artificial Intelligence as data exists in most industries/edge in the form of isolated pockets with privacy constraints for sharing the data for training an AI model. While transferring data from edge storage to a centralized cloud for training -many problems arise. Performance issues, cost and security or regulatory compliance are some of them. I’ll then walk through detailed features of federated learning combined with Blockchain to solve the above mentioned problems . Next I'll explain the advantages of modern consortium blockchains which require decentralized data storage for validating transactions securely with examples of some of the decentralized data storage platforms across a global P2P network and some of the inherent problems related to storage size and distribution.I will explain the idea of combining AI and Blockchain for mutually benefiting solutions and how they overcome challenges in each - block chain to use for consensus and decision making in AI as well as AI for optimizing storage and overcoming challenges in Blockchain - with a careful grouping of storage/transactions . I'll also showcase some of the use cases with merits of the above approach to future digitization and automation - performance and security challenges.

Mhamed Kottilungal

Sr Architect

MSys Technologies