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Cloud-first isn’t enough anymore. Unlock cost-effective AI in a hybrid- and multi-cloud world.

Enterprise companies have been moving to the cloud and are now pushing to use generative AI. However, the cloud costs get out of hand quickly, and fine-tuning Large Language Models (LLMs) is expensive and is very resource intensive to train, test, deploy, and run these models in the cloud. 

Join us live as Cloudera,  Domino Data Lab, and NVIDIA  deep dive into strategies and best practices to build a hybrid data architecture that maximizes the value of your AI initiatives. 

The panel will discuss how you can: 

  • Run your AI and LLM  in the most cost-effective manner

  • Unlock the power of cloud-native architecture with vendor-agnostic solutions

  • Stay ahead of the evolving hybrid and multi-cloud computing landscape 

  • Carefully assess your specific needs and requirements before choosing the right architecture


Chief Strategy Officer, Cloudera

Abhas Abhas


As chief strategy officer, Abhas leads the overall corporate strategy for Cloudera and is responsible for creating the company vision, building the business and customer target operating model, communicating that with key stakeholders via clearly defined OKRs, and executing key transformational initiatives to realize that plan. He’s also tasked with driving growth and innovation and making appropriate build/buy partner decisions, including pricing and packaging, corporate development, and Cloudera’s innovation accelerator to launch new products. Previously, he served as chief of staff and vice president for business transformation at the company. Prior to the Cloudera/Hortonworks merger, he helped scale Hortonworks’ go-to-market efforts as global head of customer innovation and value management. A management consultant by training, he is passionate about driving action and change in the society and has led projects with multiple organizations including the World Economic Forum, Founders of the Future, and other nonprofits.

SVP, Product Marketing, Cloudera

Luke Roquet

Chief Operating Officer, Domino Data Lab

Thomas Robinson


Thomas Robinson is the Chief Operating Officer at Domino Data Lab. He is responsible for marketing, sales, and partners. He previously acted as Domino’s VP of Strategic Partnerships and Corporate Development, developing offerings which provide differentiated value with Domino’s ecosystem. He also previously acted as Chief People Officer, responsible for building an organization to accomplish Domino’s mission of unleashing data science to address the world’s most important challenges. Prior to Domino, Thomas worked at Bridgewater Associates driving strategic transformation efforts for the firm, working first as a director in Bridgewater’s Core Technology Department to define the next generation of enterprise architecture then as a General Manager focused on recruiting and retaining technical talent.

Sr. Director, Data Science, NVIDIA

Scott McClellan


Scott directs the Data Science Business Unit for NVIDIA, driving product management; product strategy and roadmap; and partner, ecosystem, and customer engagement. Previously, Scott held CTO and chief architect roles at PRGX,, Red Hat, and HP. Scott has broad experience across machine learning, AI, big data, and numbers enterprise computing topics. Scott has a B.S. in computer science from the University of Iowa.


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