Scalable AI for Good
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<p>As AI becomes more ubiquitous and scalable we aim to apply these technologies to help improve the planet. This talk will explore Microsoft's latest contributions to the Apache Spark and Machine Learning communities with a special focus on AI for environmental and social impact. In particular, we will share how to use Azure Databricks, Azure Machine Learning and Microsoft ML for Apache Spark to explore over 5,000 years of human creativity with the Metropolitan Museum of Art, and how Microsoft uses Apache Spark to help the protect endangered species.</p>
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Scalable AI for Good
- 1. Microsoft’s AI for Good Initiative Cultural Heritage Earth Accessibility Humanitarian Action
- 2. Microsoft’s AI for Good Initiative Cultural Heritage Earth Accessibility Humanitarian Action
- 3. AI for Cultural Institutions
- 4. Celebrating 2 years of Open Access at The MET https://gen.studio 400k images released under the Open Access license
- 5. Celebrating 2 years of Open Access at The MET https://gen.studio Over 5000 years of human culture
- 6. Goals Let visitors create new works https://gen.studi o Real or Generated? Noise Vector Generator Generated Image Training Data Discriminator Real or Generated?
- 7. Goals Let visitors create new works Azure Machine Learning service Build appCollaborate Release app Monitor app ML Ops
- 8. Goals Let visitors create new works
- 9. Goals Let visitors create new works See the collection in new ways Kameyama, Yuki Hare Utagawa Hiroshige
- 10. Goals Let visitors create new works See the collection in new ways
- 11. Goals Let visitors create new works See the collection in new ways The Bracelet Thomas S. Cummings
- 12. Goals Let visitors create new works See the collection in new ways Help people explore
- 13. Intelligent Search Engine Creation Azure SearchAzure Cognitive Services MMLSparkAzure Databricks +
- 14. Microsoft Machine Learning for Apache Spark Microsoft’s Open Source Contributions to Apache Spark www.aka.ms/spark Azure/mmlspark Distributed Machine Learning Fast Model Deployment Microservice Orchestration Multilingual Binding Generation v1.0-rc
- 15. Goals Let visitors create new works See the collection in new ways Help people explore
- 17. AI for Earth
- 19. Remote Camera Trapping Which photo has a leopard?
- 20. Remote Camera Trapping > 20,000 hours
- 21. Semi Supervised Object Detection Bing Images on Spark
- 22. Semi Supervised Object Detection Bing Images on Spark Labelled Data Labelled Classification Dataframe
- 23. Semi Supervised Object Detection Labelled Dataframe MMLSpark Deep Image Classifier
- 24. Identifying Individual Leopards Source: HotSpotter - Patterned Species Instance Recognition
- 25. Semi Supervised Object Detection Model Interpretation with LIME on Spark
- 26. Semi Supervised Object Detection Model Interpretation with LIME on Spark
- 28. Microsoft’s AI for Good Initiative Cultural Heritage Earth Accessibility Humanitarian Action Seeing AI
- 29. Microsoft’s AI for Good Initiative aka.ms/ai-for-good $115 million Apply for grants at
- 30. Learn More MMLSpark aka.ms/spark AI for Good aka.ms/ai-for-good Azure ML aka.ms/azureml Azure Databricks aka.ms/azure- databricks Cognitive Services aka.ms/cognitive- services Sessions CyberML 14:40 Emerald MLFlow 15:30 Emerald AzureML + MLFlow 16:40 E103 Check online for yesterdays talks on: .NET for Spark, Data Reproducibility, Encrypted Computation, CosmosDB