Worldwide Presence India, 2005
New England, 2008 Redmond, 1991
Cambridge, UK 1997
Beijing, 1998
Silicon Valley, 2001
New York, 2012
COMPUTING CLIENT+CLOUD CONTINUOUS EVERYWHERE SENSING
Trends
NEW DATA MODELS Big Data
NATURAL USER INTERFACE
Seamless Rich Social Media Virtual Sky and Earth Web application for science and education
Goals Integration of data sets and one-click contextual access Easy access and use Tours for sharing information/insights Spatial/temporal visualization of 3D datasets
Updates API for extensibility Excel Add-in for easy data integration
Not just for Astronomy – Earth Focused Being used in Planetariums – Cal Academy
We invite you to experience it! www.worldwidetelescope.org
WORLDWIDE TELESCOPE AT TED2014 30 year Celebration and Anniversary Vancouver, BC March 17th – 21st EXPERIENCE - From neurons to space
WorldWide Telescope was invited to showcase “From neurons to space”: a virtual reality experience by Amy Robinson (MIT Media Lab, Sebastian Seung’s Lab) and Jonathan Fay (Microsoft Research) www.worldwidetelescope.org
GLIMPSE360 Control SDK Planet Explorer Sample HTML5 Client Researching at scale Let scientists be scientists….
Let scientists be scientists….
Use laptops & desktop computers Overwhelmed by data
Finding analysis ever more difficult; sharing even harder A new way of doing Research
Cloud Engagement Research
Protein Folding Civil Protection Magnetotellurics INRIA “fMRI Brain Infoplosion & Emergencies Platform Imaging on Azure”
The University of University of the Using Azure at the Premier information Predicate-Argument Washington Baker Aegean University of Adelaide technology research Structure Analysis at Laboratory laboratory Kyoto University
Windows Azure for Research Training two-day workshops
Technical resources & curriculum Research community engagements
www.azure4research.com http://www.sketchplanations.com/ Complexity
Data Science is far too complex today
• Access to quality ML algorithms, cost is high. • Must learn multiple tools to go end2end, from data acquisition, cleaning and prep, machine learning, and experimentation. • Ability to put a model into production.
This must get simpler, it simply won’t scale! Microsoft & Machine Learning 20 years of realizing innovation
1999 2004 2005 2008 2010 2012 2014
Computers Microsoft SQL Server Bing Maps Microsoft Successful, Microsoft work on users search engine enables data ships with ML Kinect can real-time, launches Azure behalf, filtering built with mining of traffic- watch users speech-to- Machine junk email machine databases prediction gestures speech Learning, learning service translation making years of innovation available
Machine learning is pervasive throughout John Platt, Distinguished scientist at Microsoft products. Microsoft Research “ ” Automatic closed captions
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Features and Benefits Reduce complexity to broaden participation • Accessible through a web browser, no software to install; • Collaborative work with anyone, anywhere via Azure workspace • Visual composition with end2end support for data science workflow; • Best in class ML algorithms; • Extensible, support for R OSS. Features and Benefits
Rapid experimentation to create a better model
• Immutable library of models, search discover and reuse; • Rapidly try a range of features, ML algorithms and modeling strategies; • Quickly deploy model as Azure web service to our ML API service. Researchers easily access results: PowerBI/ from anywhere, on any device Web Apps Mobile Apps Dashboards
ML API service and the Developer • Tested models available as an url that can be called from any end point
Azure Portal & ML API service ML Studio HDInsight and the Azure Ops Team and the Data Scientist • Create ML Studio workspace • Access and prepare data • Assign storage account(s) • Create, test and train models Azure Storage • Monitor ML consumption • Collaborate • See alerts when model is ready • One click to stage for • Deploy models to web service production via the API service Desktop Data http://aka.ms/MSRAzureML q Big Data q Machine Learning q Visualiza on q Cloud Services
Thank-you WorldWide Telescope - @WWTelescope www.worldwidetelescope.org
Microsoft Azure for Research www.azure4research.com
Azure Machine Learning http://aka.ms/MSRAzureML