Sep 9–12, 2019
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Urs Köster

Urs Köster
Head of Machine Learning, Cerebras Systems

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Urs Köster is the head of machine learning at Cerebras Systems, where he develops novel deep learning algorithms to enable the next generation of AI. He has 15 years of experience in neural networks and computational neuroscience, contributed to machine learning frameworks, developed low-precision numerical formats, and led data science engagements. Previously, he was head of algorithms R&D at Intel Nervana and a researcher at UC Berkeley.

Sessions

11:05am11:45am Wednesday, September 11, 2019
Location: 230 C
Urs Köster (Cerebras Systems)
Average rating: *****
(5.00, 1 rating)
Long training times are the single biggest factor slowing down innovation in deep learning. Today's common approach of scaling large workloads out over many small processors is inefficient and requires extensive model tuning. Urs Köster explains why with increasing model and dataset sizes, new ideas are needed to reduce training times. Read more.
  • Intel AI
  • O'Reilly
  • Amazon Web Services
  • IBM Watson
  • Dataiku
  • Dell Technologies
  • Intuit
  • Gamalon
  • H2O.ai
  • Hewlett Packard Enterprise
  • MapR Technologies
  • Sisu Data
  • Intuit

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