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Optimizing for efficiency with IBM’s Granite

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Manage episode 471358243 series 2385063
Content provided by Changelog Media and Practical AI LLC. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Changelog Media and Practical AI LLC or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

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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312 episodes

Artwork
iconShare
 
Manage episode 471358243 series 2385063
Content provided by Changelog Media and Practical AI LLC. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Changelog Media and Practical AI LLC or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

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:

Links:

  continue reading

312 episodes

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