This talk delves into the forefront of AI reliability, presenting sophisticated strategies that address core challenges in the field. Our focus encompasses the intricacies of hallucination prevention, the refinement of data batching processes, and the criticality of compliance in AI development. Leveraging deep insights from cutting-edge research and practice, we offer a comprehensive perspective on enhancing AI systems' accuracy and ethical integrity. This discourse is designed to equip practitioners and researchers with advanced methodologies, fostering the next wave of AI innovations grounded in robustness and responsibility.
Sai Teja Akula
With over a decade of dedicated experience in the field of Artificial Intelligence, Sai stands at the forefront of implementing and leveraging Data Science within organizations. A respected figure in the AI community, Sai has played an instrumental role in the transformation of traditional business models by seamlessly integrating advanced data-driven solutions. His expertise extends from developing sophisticated machine learning algorithms to strategizing the holistic implementation of AI within organizational infrastructures