Optimizing for efficiency with IBM’s Granite

We often judge AI models by leaderboard scores, but what if efficiency matters more? Kate Soule from IBM joins us to discuss how Granite AI is rethinking AI at the edge—breaking tasks into smaller, efficient components and co-designing models with hardware. She also shares why AI should prioritize efficiency frontiers over incremental benchmark gains and how seamless model routing can optimize performance. 

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Creators and Guests

Chris Benson
Host
Chris Benson
Cohost @ Practical AI Podcast • AI / Autonomy Research Engineer @ Lockheed Martin
Optimizing for efficiency with IBM’s Granite
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