Small models don’t need more parameters, they need better data. I’ll share how my team built the xLAM family of small action models that punch far above their weight, enabling fast and accurate AI agents deployable anywhere. We’ll explore why high-quality, task-specific data is the ultimate performance driver and how it turns small models into powerful, real-world solutions. You’ll leave with a practical playbook for creating small models that are fast, efficient, and ready to deploy from the edge to the enterprise.
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"Panel": Is the Future Small?
2025-11-05
George Fraser
(Fivetran)
,
Shelby Heinecke, PhD
(Salesforce)
,
Joe Reis
(DeepLearning.AI)
,
Benn Stancil
(ThoughtSpot)