Enterprises are past asking whether LLMs work; the harder question is how to run them at scale without becoming dependent on a single model, cloud, or chip vendor — and without running out of power or data-center capacity in the process.

 

In this episode, Rodrigo Liang, Co-founder and CEO of SambaNova, examines why sovereignty and business continuity now anchor enterprise infrastructure strategy, why regulated firms are keeping customer data inside their own firewalls as a first step, and why the enterprises moving fastest are planning for 100% of the business to be AI-enabled rather than gating use cases one at a time, with host Daniel Faggella, Emerj CEO and Head of Research.

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Liang outlines the practical shifts underway: from single-vendor stacks toward breadth across models, clouds, and chip architectures, from black-box outputs toward agentic workflows with checkable steps, and from scattered pilots toward code generation as the first use case that reveals what AI at scale will cost.

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To go deeper on this topic and learn how leading organizations approach AI investment more like a venture portfolio, and why interdisciplinary collaboration is critical to defining the right data for AI success, download our free PDF report, “Beginning with AI,” at emerj.com/aik4