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Why your enterprise AI strategy needs both open and closed models: The TCO reality check
Learn how enterprises evaluate open versus closed AI models to optimize costs, security, and performance across different business use cases.
Gupta explained that closed source providers typically offer several wrappers around their model that enable ease of use, simplified scaling, more seamless upgrades and downgrades and a steady stream of enhancements. Ryan Gross, Head of Data & Applications at cloud native services provider Caylent told VentureBeat that from his perspective, licensing terms don’t matter, except for in edge case scenarios. First, audit your current AI workloads and map them against the decision framework outlined by the experts, considering accuracy requirements, latency needs, cost constraints, security demands and compliance obligations for each use case.
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