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The Learning Curve: Scaling Up Document Processing

Posted Jun 23
# Tech Talk
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SPEAKERS
 Prathik Naidu
 Prathik Naidu
Prathik Naidu
Product @ Scale AI

Prathik is currently a forward deployed engineer at Scale AI, where he leads customer-facing product and engineering development for Scale Document. He has a background in machine learning research and holds a master's and bachelor's degree in computer science from Stanford University.

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Prathik is currently a forward deployed engineer at Scale AI, where he leads customer-facing product and engineering development for Scale Document. He has a background in machine learning research and holds a master's and bachelor's degree in computer science from Stanford University.

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Alexandre Matton
Alexandre Matton
Alexandre Matton
Machine Learning Research Engineer @ Scale AI

Alexandre is currently a machine-learning engineer at Scale AI, where he leads the architecture and development of new models to support new document types. He holds a master’s degree in computational and mathematical engineering from Stanford, and a bachelor’s degree in mathematics and computer science from École Polytechnique in France.

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Alexandre is currently a machine-learning engineer at Scale AI, where he leads the architecture and development of new models to support new document types. He holds a master’s degree in computational and mathematical engineering from Stanford, and a bachelor’s degree in mathematics and computer science from École Polytechnique in France.

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SUMMARY

Large industries like financial services, logistics, healthcare, and the government still run on paper documents. At Scale AI, we are building adaptive machine-learning models to scale up document processing without putting the burden on the customer. In this Tech Talk, we discuss the challenges inherent in document processing and share our development process from designing new datasets to iterating on model performance.

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Posted Jul 14 | Views 645
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