harley davidson

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Abstract Universities need to think about new academic structures for computing and information science and implement the best ideas. Cornell is trying something new. I will describe it and explain it’s rationale. Intel played a role which I will describe.

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Outline What is the problem that requires new structures? What is Cornell doing? What is a rationale for action? Conclusion

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Outline What is the problem that requires new structures? - What is the opportunity in CIS? What is Cornell doing? - Similar plans are emerging elsewhere. What is a rationale for action? - A look behind the Information Revolution. Conclusion

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Outline What is the problem that requires new structures? What is Cornell doing? What is a rationale for action? Conclusion 

Slide 6: 

What is the problem? “looming national crisis” identified in 1999 Chronicle of Higher Ed. CS Dept. enrollments are high and climbing demand for collaborations and advice is high society’s need for university research is largeComputer science as a discipline is not widely understood nor appreciated even within the academy, making judgments about it difficult and consensus rare and narrow. In particular, few people see the underlying issues and opportunities clearly. These problems are symptoms.

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“looming national crisis” identified in 1999 Chronicle of Higher Ed. competition for talent is fierce. - 500K IT job openings - all faculty can easily move (to green pastures) - potential faculty and grad students have excellent alternatives. What is the problem?

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CS enrollments are high and climbing (see graph) - high faculty work loads (teaching, advising, staying current, managing, students taught, prog courses expand) - TA shortages fewer grad students, more research funds What is the problem?

Slide 9: 

Academic Year Graduating Seniors in CS at Cornell

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What is the problem? demand for collaborations and advice is high both inside and outside universities. - NSF, KDI, ITR requirements - DARPA identifies critical problems - corporations want help - time spent on proposals exceeds returns

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society’s need for university research is large many hard problems - reliability and security - networks - bioinformatics - telemedicine - “nanoinfotech” long term solutions are needed - industry has limited horizon - industry has limited environment What is the problem?

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What is the problem? CS is not really a science or an academic field (1997 Task Force faced this view). Can just use more NA people to teach computing (58 engineers at Cornell think they “do CS”). It’s just the technology and programmers that we need. Every field will do its own computing, just as Physics always had. Computer science is not well understood, so planning for it is contentious.

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Outline What is the problem that requires new structures? What is Cornell doing? What is a rationale for action? Conclusion 

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1997 Research Futures Task Force in Science 1997 Digital Futures Committee 1999 Computing and Information Science Task Force How did Cornell respond?

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1997 Research Futures Task Force in Science - Broad and large university committee 1997 Digital Futures Committee - Eng focus, CS and EE thrust 1999 Computing and Information Science Task Force - Broad university committee How did Cornell respond?

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CIS University Task Force Report* “We believe that Cornell should create a central home for computing and information research and education, spanning the entire campus.” new courses new concentrations new majors enabling new research university wide possibly new units * www.cs.cornell.edu Quick Links

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CIS Task Force Report recommends a new kind of academic home - a faculty. which is NOT: 1. Single large dept Eng Arts Univ-level 2. Center or Laboratory 3. Division 4. College (CMU, Georgia Tech, )

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Attributes of a Faculty undergraduate teaching role with majors in several colleges (CAS, Eng, CALS ). minors and concentrations in focal areas, across colleges. undergraduate computing program, like Knight Writing Program. regular faculty, CS and beyond faculty in common with other units, “members of the FCI” independent budget managed by dean-level person. fund raising functions.

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Bringing Ideas from Computing and Information Sciences to Bear on Disciplines Across Cornell Digital Artsand Culture HumanCenteredSystems ComputationalScience Arts andHumanities SocialSciences Science andEngineering ComputerScience“Core” ComputerEngineering (EE) Applied Math (CAM) ComputerGraphics(PCG) Film andVideo Interactive Media (IMG) CognitiveStudies Economics ComputationalBiology ComputationalNeuroscience DigitalLibraries

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Opposing Views it is Information Technology that is pervasive and critical, not Information Science (which is not even a real subject). CS is not a real science and it has a service mission like mathematics that makes it appear more important than it is. Physics is the right model, CS will be the “new physics”, have a small dept. with many applied units, labs, centers, depts. other subjects are more important, e.g. the environment, astronomy, biology, materials. “eegad they are right”, CS will take over everything, we must stop them.

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CIS Task Force is mainly right, must go forward create office of CIS to figure out details (but consult Senate) go slowly, don’t let CS have all the money University Faculty Senate Views

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Outline What is the problem that requires new structures? What is Cornell doing? What is a rationale for action? Conclusion 

Slide 23: 

Cornell has recognized Computing & Information Science Task force on Strategic Research Initiatives recognized three areas as enabling - Information Sciences Genomics Advanced Materials Information science is critical to the other two. Actions taken in Genomics, Advanced Materials. CIS Task Force is operating to plan action for Information Sciences.

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Rationale - the key judgement Computing and information science is now relevant to every academic discipline at Cornell. CS Vision statement from 1995 reflects this: “In the great American universities of the 21st century it must be possible for any student to bring to bear on any subject the ideas and technology of computer science.”

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Evidence What is the evidence for this judgement? relevance “game” Information Revolution

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NSF role CISE programs KDJ ITR

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Intel role Technology for Education 2000 Projects Role of CSD in T4E

The Projects : 

The Projects Computer Science - Quality of Service - Scalable, Secure Computing - Structured Access to Information - Computational Clusters Engineering - EE – Semiconductor-Processing CAD & 3D MEMS Simulation - Mechanical Applications - ChemE Simulations - Algorithms for Engineering Simulations - Operations Research - Environmental Computing Computer Graphics & Digital Libraries Physical Science - Materials Science - Solving Quantum Chromodynamics

The Projects – Continued : 

The Projects – Continued - Training Physics PhDs - Instructional Physics Simulations - Condensed-matter Physics - Computational Chemistry - Mathematical Computing Environment Biotechnology - Computational Biology - Bioinformatics - Biometrics - Biomedical and Food Process Engineering - Predicting Effects of Technological and Regulatory Change Business and Arts - Parker Center for Investment Research - Digital Arts - Architectural Design

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Communication Computation Data CIS lives in here, the space is cyberspace. It is essentially expanding – an endless frontier. InformationTechnology Software technology exponentials Hardware technology exponentials Relation to Technology

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The Information Revolution - obvious manifestations The new economy Information corporations: Microsoft, Oracle, … Information service industry: Amazon.com, theGlobe.com 1/3 of US economic growth since 1992 7.4 million Americans at wages 60% above average E-commerce is booming (expect $1.3 Trillion by 2003): CISCO, Compaq

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New world Explosion of information on the Web: 5M domain names, .5M servers, 30M computers connected, a million new pages per day! We are connected - live in cyberspace We are not alone - “digital companions” The Deep Blue machine is world chess champion The Information Revolution - obvious manifestations

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Scientific Basis - CIS is the intellectual core The Internet Packet communications Protocols (TCP/IP) Web/Mobile code Java programming language High-level PL’s research Cryptography Computational complexity theory Intractable problems E-business Security Cryptography

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Multimedia Data compression algorithms Computational geometry Search engines Vector space model Computational graph theory Natural language technology Computational Science Parallel compilation Cluster computing Theory Center role Cognitive Science Computational theory of mind Intelligent systems Robots

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Comparison to the Industrial Revolution Science and technology create new sources of wealth- in waves Driven by physical sciences (steam, electricity, atomic energy, advanced materials) New educational institutions - military engineering, civil engineering, led to engineering colleges Massive social change - automobile vs. computer

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Scientific Revolution From moving atoms to moving bits (books, tapes, CD’s, movies, models) Founded on laws of computation and information - the theory Ideas are realized in software – experiments There has been a paradigm shift, a new “system of thought”

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Fundamental abstractions of CIS digital abstraction Von Neuman machine universal (Turing) machine symbolic computing / automatic translation theory of algorithms / data / complexity process / transaction abstraction

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The computational theory of mind AI and Cognitive Science have created a new theory of mind - major awakening of imagination (Pinker quote1) - general definition of mind (Pinker quote2) - predictive power in psychology - mentalistic language of CIS

Slide 39: 

Steven Pinker, How the Mind Works “For I believe that the discovery by cognitive science and artificial intelligence of the technical challenges overcome by our mundane mental activity is one of the great revelations of science, an awakening of the imagination comparable to learning that the universe is made up of billions of galaxies or that a drop of pond water teems with microscopic life.” - Steven Pinker, How the Mind Works, p.4 Quote

Slide 40: 

“The mind is a system of organs of computation, designed by natural selection to solve the kinds of problems our ancestors faced in their foraging way of life, in particular, understanding and outmaneuvering objects, animals, plants, and other people.” - Steven Pinker, How the Mind Works, p.21 Steven Pinker, How the Mind Works Quote

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Ann Treisman visual experiments Green 0 in sea of blue. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

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Ann Treisman visual experiments One 0 in sea of X’s. X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X 0 X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

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Ann Treisman visual experiments Green and 0. X 0 0 X 0 X 0 X 0 X 0 0 X X 0 0 X 0 0 X X 0 0 0 0 X 0 0 0 X 0 0 0 0 X X 0 X X X 0 0 0 X 0 0 0 0 0 0 0 X 0 0 0 0 X X 0 0 0 0 0 0 0 X X X 0 X 0 0 X 0 0 0 X 0 0 0 0 0 X 0 0 X 0 X X 0 0 X 0 X 0 0 0 0 0 0 0 0 0 0 0 X X 0 X 0 0 X 0 0 X 0 0 X 0 0 0 0 0 X X X X X 0 X 0 X 0 0 X 0 X X X 0 X 0 0 X 0 0 0 0 0 0 0 X X 0 0 0 0 0 X 0 0 0 0 X 0 0 0 0 0 0 0 X X 0 X 0 0 0 X 0 0 0 0 0 0 X X 0 0

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Ann Treisman visual experiments predict – focusing on one location causes peripheral features to float unattached – color and shape – same with letters in words in peripheral vision as in “the World’s Worlds Coffee”

Slide 45: 

How many F’s Finished files are the result of years of scientific study combined with the experience of years.

Slide 46: 

Fly to London Virgin

Slide 47: 

Talking about computer systems Why isn’t my computer printing? Because the OS does not know that you replaced your dot-matrix printer with a laser printer; it still thinks it’s talking to a dot-matrix printer and is waiting for an acknowledgement from the printer. But the printer is ignoring the message; it does not understand it, because it expects it to begin with a %. You need to get the attention of the OS.

Slide 48: 

Nuprl as an intelligent agent It’s successes embolden us to talk about “how Nuprl thinks.” Example 1. My gosh, it realized that x:A.B was decidable and performed a case analysis, how did it know that? E

Slide 49: 

Nuprl as an intelligent agent Example 2. Did Nuprl prove all the other subgoals? No, it doesn’t believe that E is an equivalence relation, so it asked a lot of questions I didn’t expect. What is it asking about? It wants to know why certain values are in range? What values? Only those that change the security level. It should know that, the value is in range. That is a require- ment of the decryption function. That’s part of the contract for that process.

Slide 50: 

Example 2. (cont …) Yes, but Nuprl claims that the argument to the decryption function is not of the right type. But that can’t be, ask it to explain why it is not of the right type. It reports that if process Q sent its message M with the decrypt argument just before monitor M failed, then Q could have used an undetected modular equivalence to generate the message value. Well I’ll be darned. We all missed that. Nuprl as an intelligent agent (cont …)

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Conclusion CIS is emerging as one of the major intellectual disciplines of the next century. Its scope in university terms will be at the scale of colleges not departments or centers. CIS as a body of knowledge occurs early in the “tree of knowledge” with consequences for nearly all other subjects and disciplines.

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CIS has the character of science, quantitative mathematical, predictive; the character of technology, practical, constructive, with an engineering component and the character of art, shaped by elegance and beauty and loosely constrained by laws limited largely by imagination. CIS is a bridge between the humanities and arts and the sciences as we see most clearly in the computational theory of mind. Conclusion (cont …)