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Conferences / ScaledML (Scaled Machine Learning Conference)

ScaledML 2019

Mar 27–28, 2019 · Computer History Museum, Mountain View, CA, United States

Conference
ScaledML (Scaled Machine Learning Conference) Data science & ML
Dates
Mar 27, 2019 – Mar 28, 2019
Venue
Computer History Museum
Place
Mountain View, CA, United States
Format
In person
Status
Past
Attendance
—
Website
scaledml.org
Recorded
10 sponsors · 18 speaker appearances
Notes
4th annual ScaledML. Two days of talks plus a poster session (posters by VMware, Salesforce, Uber, Adobe, Intel, Nvidia, Samsung). 'Keynote' role assigned to the hour-long slots (Patterson, Dally, Blum, Stoica, Getoor, Sutskever); the site does not label keynotes. The site said 2019 was the first year sponsors were accepted; sponsor logos shown without tiers. Ticket prices not found (Eventbrite page not archived). Talk recordings/slides are on Matroid's 2019 media archive page but not individually linkable.

Ticket prices

No ticket prices recorded

Sponsors 10

Title / headline 1

Other 9

Speakers and talks 18

SpeakerCompanyRoleTalkLinks
Bill DallyNVIDIA & StanfordKeynoteAccelerating AI—
David PattersonUC Berkeley & GoogleKeynoteDomain-Specific Architectures for Deep Neural Networks—
Ilya SutskeverOpenAIKeynoteGPT-2—
Ion StoicaUC Berkeley & DatabricksKeynoteAI and Systems at RISELab—
Lise GetoorUC Santa CruzKeynoteResponsible Data Science—
Manuel BlumCarnegie Mellon UniversityKeynoteTowards a Conscious AI: A Computer Architecture inspired by Neuroscience—
Adam D'AngeloQuoraSpeakerMachine Learning Trends and Quora—
Clement FarabetNVIDIASpeakerInside Nvidia's AI Infrastructure for Self-Driving Cars—
Dawn SongUC BerkeleySpeakerAI and Security: Lessons and Future Directions—
Dmytro DzhulgakovMetaSpeakerPyTorch at Facebook Scale—
Matei ZahariaDatabricks & StanfordSpeakerMLFlow: an introduction—
Nicolo FusiMicrosoftSpeakerTowards More Automated and Ethical Machine Learning—
Pete WardenGoogleSpeakerRunning ML Models in less than 100KB on Embedded Devices—
Reza ZadehMatroid & StanfordSpeakerScaling Computer Vision across AI chips and the Cloud—
Simon KnowlesGraphcoreSpeakerDesign Considerations for Large Learning Machines—
Srinivas NarayananMetaSpeakerAI at Scale at Facebook—
Supreet OberoiOracleSpeakerComputer Vision Applications using Matroid at Oracle—
Wei LiIntelSpeakerPerformance Software for Deep Learning—

Sources