Agencies are rapidly investing in AI and machine learning (ML) to enhance mission readiness and operational efficiency. However, fragmented data ecosystems, governance complexities, and uncertainty on how to move from pilot to production can present challenges to scaling AI effectively.
This session showcases how a unified MLOps platform and strategy can provide a scalable and secure foundation for operationalizing AI.
Key Takeaways Include:
Director of Gen AI
Machine learning principal investigator and sector chief software architect specializing in complex algorithm implementation--specifically in the machine learning arena. Has applied statistical and machine learning background to a wide range of problems, including text analysis, image processing and advanced discrimination algorithms.
Field chief data scientist
Jarrod Vawdrey is a fixture in the data science community, and is Advisor and former CEO of A42 Labs, a leading provider of AI and ML software and services for building, deploying and managing business critical data workloads at scale. Jarrod holds multiple patents in the field of AI and data science.
Sales Engineer
Dr. Andrea Lowe is a data scientist, engineering leader, and research scientist who leads customer success for government agencies, at Domino. She has led project collaborations with both industry and government, and her recent projects involved statistical analysis of large data sets to evaluate the effectiveness of a rodent-size transcranial magnetic stimulator.