Optimizing for efficiency with IBM’s Granite

Practical AI

EpisodeMar 14, 202543m

Optimizing for efficiency with IBM’s Granite

Practical AI

EpisodeMar 14, 202543m

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. Featuring:Kate Soule – LinkedInChris Benson – Website, GitHub, LinkedIn, XDaniel Whitenack – Website, GitHub, XLinks:IBM GraniteIBM Granite on Hugging FaceIBM Expands Granite Model Family with New Multi-Modal and Reasoning AI Built for the Enterprise

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Making artificial intelligence practical, productive & accessible to everyone. Practical AI is a show in which technology professionals, business people, students, enthusiasts, and expert guests engage in lively discussions about Artificial Intelligence and related topics (Machine Learning, Deep Learning, Neural Networks, GANs, MLOps, AIOps, LLMs & more). The focus is on productive implementations and real-world scenarios that are accessible to everyone. If you want to keep up with the latest advances in AI, while keeping one foot in the real world, then this is the show for you!

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