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.

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Credits:

• Host/Author: Eric Hanselman
• Guest: Mike Fratto
• Producer/Editor: Feranmi Adeoshun
• Published With Assistance From: Sophie Carr, Kyra Smith, Dylan Scheible