Optimizing for efficiency with IBM’s Granite

Optimizing for efficiency with IBM’s Granite

0 Umsagnir
0
Episode
308 of 332
Lengd
43Mín.
Tungumál
enska
Gerð
Flokkur
Óskáldað efni

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 – LinkedIn • Chris Benson – Website • , GitHub • , LinkedIn • , X • Daniel Whitenack – Website • , GitHub • , X Links:

IBM GraniteIBM Granite on Hugging FaceIBM Expands Granite Model Family with New Multi-Modal and Reasoning AI Built for the Enterprise


Hlustaðu og lestu

Stígðu inn í heim af óteljandi sögum

  • Lestu og hlustaðu eins mikið og þú vilt
  • Þúsundir titla
  • Getur sagt upp hvenær sem er
  • Engin skuldbinding
Prófa frítt
is Device Banner Block 894x1036
Cover for Optimizing for efficiency with IBM’s Granite

Other podcasts you might like ...