CS 540 – Introduction to AI Fall 2015 Jude Shavlik TA: Dmitry Basavin http://pages.cs.wisc.edu/~shavlik/cs540.html

CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1 4/22/2017 Today’s Topics Administrivia The Class Home Page Moodle Piazza? Java, Eclipse IDE, and CS 367 Course Textbook (read Ch 1 and 2, Sec 18.1-18.3, Appendices A & B) Missing class, late HWs, exam dates? TA Office Hours @ Epic? A little about me … Do not email me at jshavlik@wisc.edu (use shavlik@cs.wisc.edu) Three 50-min lectures in 170 minutes Class Style Some AI History and Philosophy Machine Learning (in Lecture 2, Week 1) For next week: Read the Algorithm section of the Wikipedia page on Random Forests and Pedro Domingos' paper A Few Useful Things to Know About Machine Learning (you can access this paper for free if you are on a UW-Madison network; if you use DoIT's VPN I believe you can also access this from a non-UW network, such as a computer in your home) 9/8/15 CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1

CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1 AI  Magic Often mathematically complex algorithms But lots of data (“big data”) and simple(r) methods can work quite well! Counting lots of things can lead to intelligent behavior (HW4) Arguably AI, especially machine learning (ML), most important IT technology currently – still quite exciting after being it in for 30+ years! 9/8/15 CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1

CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1 Class Style More about engineering intelligent s/w than modeling human cognition Concrete focus, to provide context for general AI ideas “Hands on” – learn more by (actively) doing than (passively) listening Try to write some notes during class, even though Powerpoint and videos of lectures available (more later) 9/8/15 CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1

CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1 Work Load About five HWs (35% of grade), two with substantial programming Midterm (30%) – a Thursday evening? Final (35%) – Thursday evening Dec 17? Will grade more like a grad class than a ugrad class because you all have ugrad degrees I will teach more than I can test; don’t just focus on what is graded! 9/8/15 CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1

You Remember (Metcalf, 1997 and others) 10% of what you read   20% of what you hear   30% of what you see   50% of what you hear and see together   70% of what you think and say out loud   90% of what you do ??% of what you hear, see, and write down 9/8/15 CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1

Programming Knowledge Assumed For loops, arrays, scanners (to read in data) Object-oriented design (eg, trees) Stacks, queues, linked lists, hash tables Recursion (see “Programming Knowledge Assumed” slide) Trees and recursion (cs 367 topics) will be a big part of HW1 Math: partial derivatives (for neural nets); mathematical logic and prob covered in class 9/8/15 CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1

HW Schedule (tentative) HW0 – due next class, read in dataset for ML HW1 – learn decision trees (Java) HW2 – tune sets (Java), ensembles (Java), searching for solutions (paper-and-pencil) Midterm HW3 – probabilistic reasoning (Java) and case-based reasoning (paper-and-pencil) HW4 – artificial neural networks and support vector machines (paper-and-pencil) HW5 – logical rep & reasoning (paper-and-pencil) Final 9/8/15 CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1

Detailed List of Course Topics Learning from labeled data Experimental methodologies for choosing parameter settings and estimating future accuracy Decision trees and random forests Probabilistic models, nearest-neighbor methods Genetic algorithms Neural networks Support vector machines Reinforcement learning (if time permits) Searching for solutions Heuristically finding shortest paths Algorithms for playing games like chess Simulated annealing Reasoning probabilistically Probabilistic inference Bayes' rule Bayesian networks   Reasoning from concrete cases Cased-based reasoning Nearest-neighbor algorithm Reasoning logically First-order predicate calculus Representing domain knowledge using mathematical logic Logical inference Problem-solving methods based on the biophysical world Genetic algorithms Simulated annealing Neural networks Philosophical aspects Turing test Searle's Chinese Room thought experiment The coming singularity Strong vs. weak AI Societal impact of AI 9/8/15 CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1

CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1 Late HW's Policy HW's due on-line in Moodle @ 11:55pm You have 5 late days to use over the semester (Fri 11:55pm → Mon 11:55pm is 1 late "day") SAVE UP late days! Penalty points after late days exhausted Can't be more than ONE WEEK late so solutions can be posted Since this is a class for working professionals, we’ll be a bit more flexible wrt work travel 9/8/15 CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1

Academic Misconduct (also on course homepage) All examinations, programming assignments, and written homeworks must be done individually. Cheating and plagiarism will be dealt with in accordance with University procedures (see the Academic Misconduct Guide for Students). Hence, for example, code for programming assignments must not be developed in groups, nor should code be shared. You are encouraged to discuss with your peers, the TAs or the instructor ideas, approaches and techniques broadly, but not at a level of detail where specific implementation issues are described by anyone. If you have any questions on this, please ask the instructor before you act. 9/8/15 CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1

CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1 Some AI Milestones Computer beats leading chess grand master (1997) Computer wins Jeopardy (2011) Speech recognition in smartphone (2011) Self-driving cars (2014) “Star Trek telephone” (2015) 9/8/15 CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1

The “Star Trek” Telephone Japanese Speech Recognition Machine Translation Speech Generation English 9/8/15 CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1

CS 540 at the Movies (suggest better/other videos) AI Algo Beats Kasparov at Chess https://www.youtube.com/watch?v=NJarxpYyoFI IBM Watson Wins Jeopardy https://www.youtube.com/watch?v=WFR3lOm_xhE Stanford+Google Car http://www.ted.com/talks/sebastian_thrun_google_s_driverless_car Microsoft SKYPE Translator https://www.youtube.com/watch?v=mWTySUGXR2k&list=PLD7HFcN7L XRd4kd2XgZjIbQ8TwTC32Zc9&index=3 CS 540 Nannon© Competition https://www.youtube.com/watch?v=b1SqrjuPrmE 9/8/15 CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1

DARPA Grand Challenge (2005) Oshkosh Truck came in 5th 4th: a Louisiana insurance company! Story about searching for best path through dried lake bed … Many fine paths, too much time spent thinking! What is the key difference between Chess and Jeopardy/Car-Driving? ‘closed’ vs. ‘open’ world Can you write a progam that is smarter than you? You likely will in cs540 9/8/15 CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1

Some More Videos/Images Robots Falling Down at the 2015 DARPA Robotics Challenge https://www.youtube.com/watch?v=g0TaYhjpOfo Google Translate (2015 cellphone app) 9/8/15

In which Year will Children Born that Year not Need to Learn How to Drive? Recently a leading robotics researcher said his answer is ‘2014’ Robots too polite? Eg, never speed, always yield Will existing cars be retrofitted? Will airplanes (especially freight) and trucks be first? 9/8/15 CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1

Machine Learning is Becoming Ubiquitous Search (in the Google/Bing/etc sense) Credit-card scoring, finance in general Why might “hadBankruptcy” be the best feature for deciding who gets a credit card? Personalization/recommendation in various forms Extracting ‘knowledge’ from ‘natural’ languages (Machine Reading) Understanding pictures and videos, face recognition ML large focus of CS 540 (overlap with CS 760, grad ML class) 9/8/15 CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1

An AI Axiom The easier something is for humans the harder it is for computers And vice versa A point I’ve been making for  25 years, but maybe no longer true? Human-machine cooperation appealing AI (rapidly) replacing ‘white collar’ jobs? (Robots have been replacing ‘blue collar’ jobs for awhile) 9/8/15 CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1

The Coming Singularity? 9/8/15 CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1

Some Interesting Quotes “Machine intelligence is the last invention that humanity will ever need to make.” http://www.ted.com/talks/nick_bostrom_what_happens_when_our_computers_get_smarter_than_we_are “When thinking about the future we tend to over estimate the impacts in the near-term and under estimate impacts in the long term.” Roy Amara, Institute for the Future (http://www.iftf.org/home/) 9/8/15 CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1

CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1 Linear Thinking How technology actually advances Predicted Amount of Change How we tend to predict the future Time into the Future 9/8/15 CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1

More AI Philosophy in Final Class this Term CS 540 Fall 2015 (Shavlik) 4/22/2017 More AI Philosophy in Final Class this Term Turing Test Searle’s Chinese Room story Weak and Strong AI hypotheses The future of AI including its societal impact Additional AI classes at Wisconsin 9/8/15 CS 540 - Fall 2015 (Shavlik©), Lecture 1, Week 1