![CT in Other Sciences, Math, and Engineering
Chemistry [Madden, Fellow of Royal Society of Edinburgh]
- Atomistic calculations are used to explore
chemical phenomena
- Optimization and searching algorithms
identify
best chemicals for improving reaction
conditions to improve yields
[York, Minnesota]
Geology
- “The Earth is an analogue computer.”
[Boulton, Edinburgh]
- Abstraction boundaries and hierarchies of
complexity model the earth and our atmosphere
Computational Thinking 13 Jeannette M. Wing](https://image.slidesharecdn.com/computationalthinking-110729092136-phpapp02/85/IT_Computational-thinking-13-320.jpg)
IT_Computational thinking
- 1. Computational Thinking Jeannette M. Wing President’s Professor of Computer Science and Department Head Computer Science Department Carnegie Mellon University © 2007 Jeannette M. Wing
- 2. My Grand Vision for the Field • Computational thinking will be a fundamental skill used by everyone in the world by the middle of the 21st Century. – Just like reading, writing, and arithmetic. – Imagine every child knowing how to think like a computer scientist! – Incestuous: Computing and computers will enable the spread of computational thinking. Computational Thinking 2 Jeannette M. Wing
- 3. Computational Thinking • C.T. enables what one human being cannot do alone – For solving problems – For designing systems – For understanding the power and limits of human and machine intelligence Computational Thinking 3 Jeannette M. Wing
- 4. The Two A’s of Computational Thinking • Abstraction – C.T. is operating in terms of multiple layers of abstraction simultaneously – C.T. is defining the relationships the between layers • Automation – C.T. is thinking in terms of mechanizing the abstraction layers and their relationships • Mechanization is possible due to precise and exacting notations and models – There is some “machine” below (human or computer, virtual or physical) • They give us the ability and audacity to scale. Computational Thinking 4 Jeannette M. Wing
- 5. Examples of Computational Thinking • How difficult is this problem and how best can I solve it? – Theoretical computer science gives precise meaning to these and related questions and their answers. • C.T. is thinking recursively. • C.T. is reformulating a seemingly difficult problem into one which we know how to solve. – Reduction, embedding, transformation, simulation • C.T. is choosing an appropriate representation or modeling the relevant aspects of a problem to make it tractable. • C.T. is interpreting code as data and data as code. • C.T. is using abstraction and decomposition in tackling a large complex task. • C.T. is judging a system’s design for its simplicity and elegance. • C.T. is type checking, as a generalization of dimensional analysis. • C.T. is prevention, detection, and recovery from worst-case scenarios through redundancy, damage containment, and error correction. • C.T. is modularizing something in anticipation of multiple users and prefetching and caching in anticipation of future use. • C.T. is calling gridlock deadlock and avoiding race conditions when synchronizing meetings. • C.T. is using the difficulty of solving hard AI problems to foil computing agents. • C.T. is taking an approach to solving problems, designing systems, and understanding human behavior that draws on concepts fundamental to computer science. Please tell me your favorite examples of computational thinking! Computational Thinking 5 Jeannette M. Wing
- 6. Evidence of Computational Thinking’s Influence • Computational thinking, in particular, machine learning has revolutionized Statistics – Statistics departments in the US are hiring computer scientists – Schools of computer science in the US are starting or embracing existing Statistics departments • Computational thinking is our current big bet in Biology – Algorithms and data structures, computational abstractions and methods will inform biology. • Computational thinking in other disciplines (more examples later) – Game Theory • CT is influencing Economics – Nanocomputing • CT is influencing Chemistry – Quantum computing • CT is influencing Physics Computational Thinking 6 Jeannette M. Wing
- 7. Analogy The boldness of my vision: Computational thinking is not just for other scientists, it’s for everyone. • Ubiquitous computing was yesterday’s dream, today’s reality • Computational thinking is today’s dream, tomorrow’s reality Computational Thinking 7 Jeannette M. Wing
- 8. Computational Thinking: What It Is and Is Not • Conceptualizing, not programming – Computer science is not just computer programming • Fundamental, not rote skill – A skill every human being needs to know to function in modern society – Rote: mechanical. Need to solve the AI Grand Challenge of making computers “think” like humans. Save that for the second half of this century! • A way that humans, not computers think – Humans are clever and creative – Computers are dull and boring Computational Thinking 8 Jeannette M. Wing
- 9. Computational Thinking: What It Is and Is Not • Complements and combines mathematical and engineering thinking – C.T. draws on math as its foundations • But we are constrained by the physics of the underlying machine – C.T. draws on engineering since our systems interact with the real world • But we can build virtual worlds unconstrained by physical reality • Ideas, not artifacts – It’s not just the software and hardware that touch our daily lives, it will be the computational concepts we use to approach living. • It’s for everyone, everywhere – C.T. will be a reality when it is so integral to human endeavors that it disappears as an explicit philosophy. Computational Thinking 9 Jeannette M. Wing
- 10. Two Messages for the General Public • Intellectually challenging and engaging scientific problems in computer science remain to be understood and solved. – Limited only by our curiosity and creativity • One can major in computer science and do anything. – Just like English, political science, or mathematics Computational Thinking 10 Jeannette M. Wing
- 11. Research Implications Computational Thinking 11 Jeannette M. Wing
- 12. CT in Other Sciences, Math, and Engineering Biology - Shotgun algorithm expedites sequencing of human genome - DNA sequences are strings in a language - Protein structures can be modeled as knots - Protein kinetics can be modeled as computational processes - Cells as a self-regulatory system are like electronic circuits Brain Science - Modeling the brain as a computer - Vision as a feedback loop - Analyzing fMRI data with machine learning Computational Thinking 12 Jeannette M. Wing
- 13. CT in Other Sciences, Math, and Engineering Chemistry [Madden, Fellow of Royal Society of Edinburgh] - Atomistic calculations are used to explore chemical phenomena - Optimization and searching algorithms identify best chemicals for improving reaction conditions to improve yields [York, Minnesota] Geology - “The Earth is an analogue computer.” [Boulton, Edinburgh] - Abstraction boundaries and hierarchies of complexity model the earth and our atmosphere Computational Thinking 13 Jeannette M. Wing
- 14. CT in Other Sciences, Math, and Engineering Astronomy - Sloan Digital Sky Server brings a telescope to every child - KD-trees help astronomers analyze very large multi-dimensional datasets Mathematics - Discovering E8 Lie Group: 18 mathematicians, 4 years and 77 hours of supercomputer time (200 billion numbers). Profound implications for physics (string theory) - Four-color theorem proof Engineering (electrical, civil,mechanical, aero&astro, …) - Calculating higher order terms implies more precision, which implies reducing weight, waste, costs in fabrication - Boeing 777 tested via computer simulation alone, not in a wind tunnel Computational Thinking 14 Jeannette M. Wing
- 15. CT for Society Economics - Automated mechanism design underlies electronic commerce, e.g., ad placement, on-line auctions, kidney exchange - MIT PhDs in CS are quants on Wall Street Social Sciences - Social networks explain phenomena such as MySpace, YouTube - Statistical machine learning is used for recommendation and reputation services, e.g., Netflix, affinity card Computational Thinking 15 Jeannette M. Wing
- 16. CT for Society Medicine - Robotic surgery - Electronic health records require privacy technologies - Scientific visualization enables virtual colonoscopy Law - Stanford CL approaches include AI, temporal logic, state machines, process algebras, petri nets - POIROT Project on fraud investigation is creating a detailed ontology of European law - Sherlock Project on crime scene investigation Computational Thinking 16 Jeannette M. Wing
- 17. CT for Society Entertainment - Games - Movies - Dreamworks uses HP data center to renderShrek and Madagascar - Lucas Films uses 2000-node data center to produce Pirates of the Caribbean. Arts - Art (e.g., Robotticelli) - Drama Sports - Music - Lance Armstrong’s cycling - Photography computer tracks man and machine statistics - Synergy Sports analyzes digital videos NBA games Computational Thinking 17 Jeannette M. Wing
- 18. Educational Implications Computational Thinking 18 Jeannette M. Wing
- 19. Curricula Development • Universities should start with their freshmen-level intro courses. – Teach “Ways to Think Like a Computer Scientist” not just “Intro to <programming langage du jour>” • Engage national and international organizations to reform curricula, in particular K-12. – ACM, CSTA, CRA, etc. • It needs to be a collective effort. Computational Thinking 19 Jeannette M. Wing
- 20. Adapt Course Material for Other Audiences • K-6, 7-9, 10-12 • Undergraduate courses – Freshmen year • “Ways to Think Like a Computer Scientist” aka Principles of Computing – Upper-level courses • Graduate-level courses – Computational arts and sciences • E.g., entertainment technology, computational linguistics, …, computational finance, …, computational biology, computational astrophysics • Students and teachers – CS4All: Carnegie Mellon outreach to high school teachers, counselors, and guidance counselors Computational Thinking 20 Jeannette M. Wing
- 21. Ways To Think Like A Computer Scientist • Freshmen year course • Suitable for non-majors, but inspirational for majors • Lessons – Thinking Recursively – Thinking Abstractly – Thinking Ahead (caching, pre-fetching…) – Thinking Procedurally – Thinking Logically – Thinking Concurrently – … • Problem sets: pencil-and-paper thought exercises, programming exercises Computational Thinking 21 Jeannette M. Wing
- 22. Recursion: Towers of Hanoi Goal: Transfer the entire tower to one of the other pegs, moving only one disk at a time and never a larger one onto a smaller. Computational Thinking 22 Jeannette M. Wing
- 23. Data Abstraction and Representation stack queue tree (upside down) representation invariant array and pointer Computational Thinking 23 Jeannette M. Wing
- 24. Composition and Decomposition Computational Thinking 24 Jeannette M. Wing
- 25. Sorting and Search Computational Thinking 25 Jeannette M. Wing
- 26. Intractability: Traveling Salesman Problem: A traveling salesperson needs to visit n cities. Is there a route of at most d in length? O(n!) n = 16 → 242 days n = 25 → 5x10^15 centuries Computational Thinking 26 Jeannette M. Wing
- 27. Undecidability: Tiling Can we tile the entire plane Z2? Example from David Harel Computational Thinking 27 Jeannette M. Wing
- 28. Data as Code and Code as Data unrecognized email attachment Computational Thinking 28 Jeannette M. Wing
- 29. Recursion Revisited The Y operator Y = λ f. (λ x. f (x x)) (λ x. f (x x)) which satisfies the following equation Y f = f (Y f) and is the basis of recursion in Computer Science. Y is the fixed point combinator in lambda calculus. Computational Thinking 29 Jeannette M. Wing
- 30. Correctness: Avoiding Bugs to Save Money and Lives Ariane 5 failure Intel Pentium FPU error Now Intel uses formal verification. Now Microsoft uses formal verification. Computational Thinking 30 Jeannette M. Wing
- 31. Caching knapsack locker home Computational Thinking 31 Jeannette M. Wing
- 32. Pipelining: Doing Laundry 6 hours to do 4 loads 3.3 hours to do 4 loads Computational Thinking 32 Jeannette M. Wing
- 33. Concurrency: Dining Philosophers Five philosophers sit around a circular table. Each philosopher spends his life alternately thinking and eating. In the centre of the table is a large bowl of spaghetti. A philosopher needs two forks to eat a helping of spaghetti. Computational Thinking 33 Jeannette M. Wing
- 34. Distributed Computing: The Internet • Asynchronous communication • Failures • Speed of light Computational Thinking 34 Jeannette M. Wing
- 35. Deep Questions in Computer Science • Does P = NP ? • What is computable? • What is intelligence? • What is system complexity? Computational Thinking 35 Jeannette M. Wing
- 36. The $1M Question: Does P = NP? • The most important open problem in theoretical computer science. The Clay Institute of mathematics offers one million dollar prize for solution! – http://www.claymath.org/Millennium_Prize_Problems/ NP NP- P = NP = NP-complete P complete Boolean satisfiability(SAT) N-puzzle Knapsack Hamiltonian cycle Traveling salesman Subgraph isomorphism If P ≠ NP Subset sum Clique If P = NP Vertex cover Independent set Graph coloring Computational Thinking 36 Jeannette M. Wing
- 37. What is Computable? • What is are the power and limits of computation? • What is computable when one considers The Computer as the combination of Human and Machine? Labeling Images on the Web CAPTCHAs Computational Thinking 37 Jeannette M. Wing
- 38. What is Intelligence? Human and Machine invariant representations: On Intelligence, by Jeff Hawkins, creator of PalmPilot and Treo “Computing Versus Human Thinking,” Peter Naur, Turing Award 2005 Lecture, Human vs. Machine CACM, January 2007. Computational Thinking 38 Jeannette M. Wing
- 39. What is System Complexity? Question 1: Do our systems have to be so complex? • Can we build systems with simple designs, that are easy to understand, modify, and maintain, yet provide the rich complexity in functionality of systems that we enjoy today? Further, observe: • We have complexity classes from theory. • We build complex systems that do amazing, but often unpredictable, things. Question 2: Is there a meaning of system complexity that spans the theory and practice of computing? Computational Thinking 39 Jeannette M. Wing
- 40. Grand Vision for Society • Computational thinking will be a fundamental skill used by everyone in the world by the middle of the 21st Century. • Join us at Carnegie Mellon and the entire computing community toward making computational thinking commonplace. – www.cs.cmu.edu/ct Spread the word! To your fellow faculty, students, researchers, administrators, teachers, parents, principals, guidance counselors, school boards, teachers’ unions, congressmen, policy makers, … Computational Thinking 40 Jeannette M. Wing