Inference is the execution of a trained artificial intelligence or machine learning model on new data to produce outputs such as predictions or classifications, used in enterprises to support production applications, automated decisions, and analytics within governed, monitored environments.
The blog argues that AI depends on networking, outlining scale-up, scale-out, open architectures, and vendor-agnostic planning to control AI cost per token.
Podcast discussion on building AI-era networking: moving from one fabric to multiple networks for AI factories, with openness and standardization to manage complexity and cost.
The post contrasts AI conversations in applications with performance changes in data movement, network design, telemetry, and stable operations for agents.
After Cisco Live 2026, Sameh Boujelbene analyzes how Cisco is positioning validated AI infrastructure platforms beyond standalone hardware performance and networking speeds.
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