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AI Networking
Networking can be an invisible part of IT infrastructure, but AI is creating demands that make it a critical part of keeping AI application fed with data. Mike Fratto returns to the podcast to discuss both the long haul and local requirements for AI networking with host Eric Hanselman. It’s always been important to link chunks of infrastructure efficiently, but AI’s voracious need for data has dramatically increased the scope and scale of the need. The risk that any gap in performance or capacity presents is that precious GPU resources will be idled, an increasingly expensive proposition. The realities of AI application architectures is that infrastructure is ever more hybrid, requiring access to repositories of data both on-premises and in various clouds and models scattered across various providers. The need for dynamic connectivity is driven by the rapid evolution of preferences for new models and the diversifying needs of agents to reach new data sources. It’s not only forcing network expansion, but it’s also driving M&A activity as network providers look to enhance automation in response to customer demands. More S&P Global Content: Compute sovereignty: The strategic importance of digital infrastructure AI won’t solve its own energy problem – and that might be fine AI in action: unleashing agentic potential AI infrastructure results in 2025 top expectations, forecast upgraded For S&P Global subscribers: MWC 2026: Agentic AI as the next operating model for networks and network operations AI Infrastructure Market Monitor & Forecast Service providers race to meet surging enterprise demand for AI infrastructure In 2026, the telecom network becomes code Credits: Host/Author: Eric Hanselman Guest: Mike Fratto Producer/Editor: Feranmi Adeoshun Published With Assistance From: Sophie Carr, Kyra Smith, Dylan Scheible
Next in Tech
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