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ML Scalability Challenges

Posted Apr 17, 2023 | Views 235
# ML Scalability
# Anyscale
# Attention-based Models
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SPEAKER
 Waleed Kadous
 Waleed Kadous
Waleed Kadous
Head of Engineering @ Anyscale

Dr. Waleed Kadous leads engineering at Anyscale, the company behind the open source project Ray, the popular scalable AI platform. Prior to Anyscale, Waleed worked at Uber, where he led overall system architecture, evangelized machine learning, and led the Location and Maps teams. He previously worked at Google, where he founded the Android Location and Sensing team, responsible for the "blue dot" as well as ML algorithms underlying products like Google Fit.

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Dr. Waleed Kadous leads engineering at Anyscale, the company behind the open source project Ray, the popular scalable AI platform. Prior to Anyscale, Waleed worked at Uber, where he led overall system architecture, evangelized machine learning, and led the Location and Maps teams. He previously worked at Google, where he founded the Android Location and Sensing team, responsible for the "blue dot" as well as ML algorithms underlying products like Google Fit.

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SUMMARY

Dr. Waleed Kadous, Head of Engineering at Anyscale, discusses the challenges of scalability in machine learning and his company's efforts to solve them. The discussion covers the need for large-scale computing power, the importance of attention-based models, and the tension between big and small data.

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# Challenges of Deploying ML Models
# Wallaroo
# Edge and ML