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Why fast, effective data labeling has become a competitive advantage (VB Live)
Nov 24, 2021 | Venture Beat
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Presented by Labelbox

Iterating on training data is key to building performant models, but perfecting and tightening the loop still remains a challenge for even the most advanced teams. For practical insights on how to get models to production-level performance quickly with high-quality training data, don’t miss this VB Live event.

Register here for free.

The greatest challenge faced by machine learning engineers today is the number of time-consuming steps between gathering data and having a high-performing model. These steps can be incredibly laborious, and many ML teams in enterprises lack the infrastructure or tools to do it quickly enough.

“One of the biggest learnings we’ve had over the last few decades as a community is that the cornerstone for success in technology and engineering is faster iterations,” says Manu Sharma, CEO & cofounder of Labelbox. “The reason leading AI companies are successful is they’re iterating fast. They learn from each cycle and they improve rapidly.”

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