Presentation on theme: "Managing Innovation: How Microsoft Research Works Jim Gray Distinguished Engineer Microsoft Corporation."— Presentation transcript:
Managing Innovation: How Microsoft Research Works Jim Gray Distinguished Engineer Microsoft Corporation
Actionable Ideas Co-lo if possible Adopt a university model Recruit from the top Recruit for passion and a desire to have impact Install a Research Program Management organization to orchestrate tech-transfer Institute an annual TechFest
Innovation Build versus Buy versus Invest Build: Have in-house research Bell Labs, IBM, GM, Pfizer, Merc, Microsoft… Buy: Acquire startups or whole companies IBM, Cisco, Intel, Microsoft, Pfizer, Merc… Invest: All boats rise Government research funding IBM, Cisco, Intel, Microsoft, Pfizer, Merc… All 3 approaches valid Complement one another
Companies Are Different Selected IT company FY02 R&D budgets: Notice that R&D is correlated with margin IBM and HP have large service revenues So, their real R&D investment rate is higher Dell, Accenture, EDS have modest R&D – innovate in other ways Intel R&D 15% S G&A 16% Product 19% Gross 50% Microsoft Gross 40% Product 18% S G&A 27% R&D 15% IBM S G&A 23% Product 31% Gross 38% other 2% R&D 6% Oracle R&D 12% Gross 36% Product 26% S G&A 26% HP S G&A 16% Product 44% Gross 27% other 7% R&D 6% Cisco S G&A 25% Product 33% Gross 26% R&D 16% DELL R&D 1% Gross 18% Product 73% S G&A 8% Accenture Gross 32% Product 47% S G&A 21% R&D 0% EDS S G&A 9% Product 69% Gross 8% other 14% R&D 0%
Microsoft Is Different It is a software company: Almost entirely an IP company Margins on successful products are enormous The cost of failure is enormous – missed market It is BIG and so must look for BIG bets High-velocity business: Product mix shifts every decade. If you miss a shift, you are dead.
Most R&D Is D How to Do Basic Research in Industry? Critical questions (from Rick Rashid) How can I create and maintain a world class research organization in an industrial setting? How do I keep the lines of communication open between product teams and researchers? How do I get new technology into products quickly?
Approach Adapt the Academic Model Organizational goal: Advance state of the art University organizational model Flat structure, critical mass groups Open research environment Aggressive publication in peer-reviewed literature Frequent visitors, daily seminars Strong ties to University Research Nearly 15% of basic research budget directly invested in Universities Lab grants, research grants, fellowships, etc. Hundreds of interns and visitors
Microsoft Research Today Founded in 1991 Staff of over 700 in over 55 areas Internationally recognized research teams Research lab locations : Redmond, Washington, 75% San Francisco, California 1% Cambridge, United Kingdom 10% Beijing, Peoples Republic of China 10% Mountain View, California 5%
Microsoft Research Expanding the State of the Art Thousands of peer-reviewed publications 10%…30% of papers at our focus conferences graphics, programming, systems, data management… Community leadership Professional societies JournalsConferences Mentoring Interns Hosting academic summers and sabbaticals Special workshops
How To Build A Group Identify a promising area Hire the leader (internal or external) Support her/him Build team around senior researcher Look for people who Want to have impact Have passion for their ideas Same template works for whole labs Cambridge, Beijing, Silicon Valley
Keeping Open The Lines Of Communication To Product Teams Co-location helps: 75% on campus How can I help? attitude demonstrates willingness to get dirty to help product succeed Product group spin-offs build strong ties Over time a number of product groups evolved from research (e.g., Windows Media) Researchers involved in all corporate product reviews
MSR Relationship To MS Products Virtually every research group actively engaged with product groups E.G., Windows, Office, streaming media, SQL, Exchange, IIS, commerce server, visual studio, office, consumer products, MSN, etc. Tech transfer: IdeasCodePeopleContactsRecruiting
Focused Technology Transfer Quickly getting technology into products Program management team with sole focus on tech transfer Researchers on product advisory boards Mind-swaps – joint product/research off-sites Joint product/research teams, e.g., ClearType (Windows XP) Datamining (SQL 2000) Natural Language & Speech (Office) TabletPC Smart Personal Objects (SPOT) Encourage and recognize contributions
MSR Techfest Internal open house for Microsoft Research Annual event since 2001 ~ 7000 attendees 170 demos, 26 lectures Research in progress Breadboard demos This is research idea/prototype Great networking event: Breaks down barriers Serendipitous connections.
Examples Of Technology Transfer Critical support technologies Memory Optimization Technology enabled sim-ship of Win95/Office95 Automated bug detection in Windows 2000 Key technologies that drive products E.G., MS audio 4.0, ClearType, intelligent search, collaborative filtering, Intellimirror, etc. Incubated major products Windows streaming media Windows CE, TabletPC, eBook Ecommerce, Datamining Natural language and speech technologies, etc.
MSR Mission Statement Expand the state of the art in each of the areas in which we do research Rapidly transfer innovative technologies into Microsoft products Ensure that Microsoft products have a future
Personal Examples of R&D Scaleable Servers TerraServerSkyServerDatabases Data Cube, Snapshot Isolation SQL Stress testing Reliable Multicast Personal Media Management
TerraServer & TerraService A.NET web service OpenGIS Place Search TerraServer Map Server Landmarks & annotations layered on imagery Used by thousands of real apps today Shows Web Services Performance USGS Photo and Topo maps 16TB of data Online since billon pages served 120 TB served ShowsScalabilityAvailabilityManageability SQL + Windows TerraService TerraServer
TerraServer Tomorrow Mirrored System versus SAN 3 mirrored DB servers + spare versus 4 DB servers Commodity versus Enterprise White box Dual Xeon versus 8-way branded DAS 250GB SATA versus FC-SAN 73GB SCSI No Tape versus LTO Tape Robot $0.1M versus $1.8M Geoplex: 2 sites You can afford 2! KVM / IP
World Wide Telescope Premise: Most Astro data is online So, the Internet is the worlds best telescope: Has data on every part of the sky In every measured spectral band As deep as the best instruments It is up when you are up; the seeing is always great (no working at night, no clouds no moons no…) Its a smart telescope: links objects and data to literature on them
Next-Generation Data Analysis Looking for Needles in haystacks – the Higgs particle Haystacks: Dark matter, Dark energy Needles are easier than haystacks Global statistics have poor scaling Correlation functions are N 2, likelihood techniques N 3 As data and computers grow at same rate, we can only keep up with N logN A way out? data is fuzzy, answers are approximate Requires combination of statistics and computer science
Federation Data Federations Of Web Services Massive datasets live near their owners: Near the instruments software pipeline Near the applications Near data knowledge and curation Super Computer centers become Super Data Centers Each Archive publishes a web service Schema: documents the data Methods on objects (queries) Scientists get personalized extracts Uniform access to multiple Archives A common global schema Challenge: What is the object model for your science?
Your program Web Service Web Service Web Services – The Key? Web SERVER: Given a url + parameters Returns a web page (often dynamic) Web SERVICE: Given a XML document (soap msg) Returns an XML document Tools make this look like an RPC. F(x,y,z) returns (u, v, w) Distributed objects for the web. + naming, discovery, security,.. Internet-scale distributed computing Your program soap object in xml http Web page Data In your address space Data In your address space
Federating Astronomy Archives Great Test for data mining algorithms It is real and well documented data High-dimensional data (with confidence intervals) High-dimensional data (with confidence intervals) Spatial data Spatial data Temporal data Temporal data Many different instruments from many different places and many different times Federation is a goal There is a lot of it (petabytes) Can share cross company University researchers IRAS 100m ROSAT ~keV DSS Optical 2MASS 2m IRAS 25m NVSS 20cm WENSS 92cm GB 6cm
SkyServer – One such archive SkyServer.SDSS.org SkyServer.SDSS.org Sloan Digital Sky Survey Pixels + Data Mining 400 attributes per object Spectrograms for 1% Demo: pixel space record space set space teaching
SkyQuery: Federating Archives Distributed Query tool using a set of web services Federates ten astronomy archives from Pasadena, Chicago, Baltimore, Cambridge (England) Implemented in C# and.NET Allows queries like: SELECT o.objId, o.r, o.type, t.objId FROM SDSS:PhotoPrimary o, TWOMASS:PhotoPrimary t WHERE XMATCH(o,t)<3.5 AND AREA(181.3,-0.76,6.5) AND o.type=3 and (o.I - t.m_j)>2 SELECT o.objId, o.r, o.type, t.objId FROM SDSS:PhotoPrimary o, TWOMASS:PhotoPrimary t WHERE XMATCH(o,t)<3.5 AND AREA(181.3,-0.76,6.5) AND o.type=3 and (o.I - t.m_j)>2
2MASS SkyQuery Portal SkyQuery Structure Each SkyNode publishes Schema Web Service Database Web Service Portal Plans Query (2 phase) Integrates answers Is itself a web service SDSSINTFIRST Image Cutout
Databases Theory to practice Data Cube Wrote paper SQL Server product and ISO Standard adopted idea Snapshot Isolation Paper in 1996 Product in 2004 Readerversion old new
Databases Stress Test Generate millions of random SQL queries Send them to 4 different products Compare the answers: If all agree, good! If not, a bug somewhere Found many bugs in DB products Much appreciated by MS DB group Tool cloned by other DB vendors Informix Oracle DB2 SqlServer =
SQL Automated Test Example Four SQL systems on 2,000 statements W X Y Z Error All four agree 84% Problem with intermediate table. Case W,X, and Y agree 95%
Reliable multicast protocol Scales using hierarchy, suppression, and FEC on-demand (FEC on-demand is our contribution) Joint work with Cisco and others IETF standard Implemented prototype (Multicast PowerPoint) Shipped in Windows XP PGM Pretty Good Multicast
MyLifeBits A lifetime store of everything The experiment: digitizing Gordon Bells life The software: Based on SQL server Tools to capture web pages, IM chats, TV, radio & telephone Reports, links, full text search, pivot by time or any other attribute
MyLifeBits Software Internet MyLifeBits store database files Voice annotation tool Text annotation tool Legacy applications MAPI interface Legacy client Radio EPG tool PocketPC transfer tool Telephone capture tool Radio capture tool TV capture tool TV EPG download tool Browser tool MyLifeBits Shell PocketRadio player
Research Failures Not everything is a success We had technology transfer failures We had projects with little impact Success and Failure depend on environment Even if you have a GREAT! idea There are many exogenous factors in technology transfer And, sometimes the idea or focus is wrong Allow people to fail once or twice.
Summary Actionable Ideas Co-lo if possible Adopt a university model Recruit from the top Recruit for passion and a desire to have impact Install a Research Program Management organization to orchestrate tech-transfer Institute an annual TechFest