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David Patterson - Domain-Specific Architectures for Deep Neural Networks
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Presented at the Matroid Scaled Machine Learning Conference 2019
Venue: Computer History Museum

scaledml.org | #scaledml2019

Reza Zadeh - ScaledML 2019 Introduction

Reza Zadeh - Scaling Computer Vision across AI chips and the Cloud

Matei Zaharia - MLflow: An Introduction

Megan Kacholia - ML at Google Scale

Matroid Product Overview

Ilya Sutskever - GPT-2

Ion Stoica - AI and Systems at RISELab

Wei Li - Performance Software for Deep Learning

Dmytro Dzhulgakov - PyTorch at Facebook Scale

Supreet Oberoi - Computer Vision Applications using Matroid at Oracle

Adam D'Angelo - Machine Learning Trends and Quora

Pete Warden - Running ML Models in less than 100KB on Embedded Devices

Bill Dally - Accelerating AI

Srinivas Narayanan - AI at Scale at Facebook

Simon Knowles - Specialized Deep Learning with Graphcore

Nicolo Fusi - Toward More Automated and Ethical Machine Learning

Lise Getoor - Responsible Data Science

Dawn Song - AI and Security: Lessons and Future Directions

Lise Getoor - Responsible Data Science

Simon Knowles - Design Considerations for Large Learning Machines

Manuel Blum - Towards a Conscious AI: A Computer Architecture inspired by Neuroscience

David Patterson - Domain-Specific Architectures for Deep Neural Networks

Clément Farabet - Inside Nvidia's AI Infrastructure for Self-Driving Cars

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