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Scaling GenAI Without Burdening the Data Center - with Greg Ratcliff of Vertiv
Manage episode 517954928 series 79750
Today's guest is Greg Ratcliff, Chief Innovation Officer at Vertiv. With 30 years of experience leading technology teams and global innovation initiatives, Gregory offers deep expertise in data, IoT, and digital infrastructure. Ratcliff joins Emerj Editorial Director Matthew DeMello to discuss how enterprise leaders can scale AI effectively by building the right infrastructure and addressing key bottlenecks. Gregory also shares practical strategies for modular, hybrid data environments, bridging talent gaps, and improving operational efficiency across AI workflows. Join an exclusive circle of AI leaders shaping the conversation in business. Share your AI adoption story and be considered as a future guest on the 'AI in Business' podcast. Apply now at emerj.com/expert2.This episode is sponsored by Pure Storage. See how your brand can partner with Emerj to share insights and reach decision-makers. Get started at emerj.com/ad1.
1058 episodes
Manage episode 517954928 series 79750
Today's guest is Greg Ratcliff, Chief Innovation Officer at Vertiv. With 30 years of experience leading technology teams and global innovation initiatives, Gregory offers deep expertise in data, IoT, and digital infrastructure. Ratcliff joins Emerj Editorial Director Matthew DeMello to discuss how enterprise leaders can scale AI effectively by building the right infrastructure and addressing key bottlenecks. Gregory also shares practical strategies for modular, hybrid data environments, bridging talent gaps, and improving operational efficiency across AI workflows. Join an exclusive circle of AI leaders shaping the conversation in business. Share your AI adoption story and be considered as a future guest on the 'AI in Business' podcast. Apply now at emerj.com/expert2.This episode is sponsored by Pure Storage. See how your brand can partner with Emerj to share insights and reach decision-makers. Get started at emerj.com/ad1.
1058 episodes
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