Operationalizing AI for Scale and Sovereignty
Companies are taking control of their own data to tailor AI for their needs, balancing ownership with safe and trusted data flow.
In the era of artificial intelligence, data has become a valuable asset for companies seeking to harness its power. However, the challenge lies in balancing ownership with the safe, trusted flow of high-quality data needed to power reliable insights. This delicate balance was a key topic of discussion at MIT Technology Review's EmTech AI conference, where experts explored how AI factories can unlock new levels of scale, sustainability, and governance.
Chris Davidson, Vice President of HPC & AI Customer Solutions at Hewlett Packard Enterprise, is at the forefront of this conversation. He leads HPE's global strategy for AI Factory solutions and Sovereign AI, working with governments, enterprises, and research institutions to build secure, scalable national- and enterprise-grade AI capabilities. According to Davidson, the goal is to position data control as a strategic imperative for governments and enterprises.
Davidson's role at HPE involves directing Product Management and Performance Engineering across the company's HPC and AI portfolio. This includes large-model training platforms and Cray exascale systems, where his teams define product strategy, performance architecture, and deployment models. With over nine years of experience at HPE, Davidson has led key initiatives across Performance Engineering, AI Cloud, and Professional Services, shaping how the company delivers optimized, cloud-native, and globally deployed high-performance systems.
Mallikarjun (Arjun) Shankar, Division Director for the National Center for Computational Science at the Oak Ridge National Laboratory, shares Davidson's passion for harnessing the power of AI and data science. His research focuses on the interdisciplinary bridge between computer science and large-scale scientific discovery campaigns that rely on scalable computing and data science. As a joint faculty appointee at the University of Tennessee's Bredesen Center, Shankar is well-positioned to drive innovation in this field.
As companies and governments navigate the complex landscape of AI, experts like Davidson and Shankar are paving the way for a more secure, scalable, and sustainable future. By operationalizing AI for scale and sovereignty, organizations can unlock new levels of growth, innovation, and discovery – ultimately driving progress in a rapidly changing world.
Source: MIT Technology Review