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Legare Kerrison and Cedric Clyburn on LLM Performance and Evaluations
Our take
Legare Kerrison and Cedric Clyburn from RedHat recently shared their insights on evaluating Large Language Model (LLM) performance at the Arc of AI 2026 Conference. They emphasized the importance of effectively measuring LLM applications to foster the adoption of AI technologies within organizations. Their discussion highlighted practical methods for optimizing LLM inference, providing attendees with actionable strategies to enhance performance. This session underscored the critical role of LLM evaluations in navigating the evolving landscape of AI and maximizing its impact on productivity and innovation.
Effectively measuring the performance of applications that are leveraging Large Language Models (LLM) is critical to the adoption of AI technologies in organizations. Legare Kerrison and Cedric Clyburn from RedHat team recently spoke at Arc of AI 2026 Conference about practical methods to evaluate and optimize LLM inference.
By Srini PenchikalaRead on the original site
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