A Few AI Achievements

Amy Greenwald, Enrique Areyan ViqueiraCS140 - Fall 2020 - The COVID year

AI Achievements

AI techniques are used in MANY places for MANY purposes.

Let’s take a walk on our syllabus for the semester.

Search

Adversarial Search in Games

Optimization

Hidden Markov Models

Supervised Learning

Unsupervised Learning

Reinforcement Learning

Natural Language Processing

Computer Vision

Multi-agent Systems

AI Achievements

AI techniques are used in MANY places for MANY purposes.

Let’s take a walk on our syllabus for the semester.

Search

Adversarial Search in Games

Optimization

Hidden Markov Models

Supervised Learning

Unsupervised Learning

Reinforcement Learning

Natural Language Processing

Computer Vision

Multi-agent Systems

}Core Topics

AI Achievements

AI techniques are used in MANY places for MANY purposes.

Let’s take a walk on our syllabus for the semester.

Search

Adversarial Search in Games

Optimization

Hidden Markov Models

Supervised Learning

Unsupervised Learning

Reinforcement Learning

Natural Language Processing

Computer Vision

Multi-agent Systems

}Core Topics

{Invited Speakers

AI Achievements - Search

AI Achievements - Search

AI Achievements - Search

AI Achievements - Search

AI Achievements - Search

AI Achievements - Adversarial Search in Games

AI Achievements - Adversarial Search in Games

AI Achievements - Adversarial Search in Games

AI Achievements - Adversarial Search in Games

AI Achievements - Adversarial Search in Games

AI Achievements - Adversarial Search in Games

AI Achievements - Adversarial Search in Games

https://vimeo.com/389556398

AI Achievements - Optimization

SAT: Satisfiability, checking whether a boolean formula e.g,

can be satisfied or not.(x1 ∨ x2) ∧ (¬x1 ∨ x3)

AI Achievements - Optimization

SAT: Satisfiability, checking whether a boolean formula e.g,

can be satisfied or not.(x1 ∨ x2) ∧ (¬x1 ∨ x3)

AI Achievements - Optimization

SAT: Satisfiability, checking whether a boolean formula e.g,

can be satisfied or not.(x1 ∨ x2) ∧ (¬x1 ∨ x3)

AI Achievements - Optimization

SAT: Satisfiability, checking whether a boolean formula e.g,

can be satisfied or not.(x1 ∨ x2) ∧ (¬x1 ∨ x3)

AI Achievements - Optimization

Also, Operations Research

SAT: Satisfiability, checking whether a boolean formula e.g,

can be satisfied or not.(x1 ∨ x2) ∧ (¬x1 ∨ x3)

AI Achievements - Hidden Markov Models

AI Achievements - Hidden Markov Models

AI Achievements - Hidden Markov Models

AI Achievements - Hidden Markov Models

AI Achievements - Hidden Markov Models

AI Achievements - Hidden Markov Models

AI Achievements - Supervised Learning

AI Achievements - Supervised Learning

AI Achievements - Supervised Learning

AI Achievements - Supervised Learning

AI Achievements - Supervised Learning

AI Achievements - Supervised Learning

AI Achievements - Supervised Learning

AI Achievements - Supervised Learning

https://thispersondoesnotexist.com

AI Achievements - Unsupervised Learning

AI Achievements - Unsupervised Learning

AI Achievements - Unsupervised Learning

AI Achievements - Unsupervised Learning

AI Achievements - Reinforcement Learning

AI Achievements - Reinforcement Learning

AI Achievements - Reinforcement Learning

AI Achievements - Reinforcement Learning

AI Achievements - Reinforcement Learning

AI Achievements - Reinforcement Learning

AI Achievements - Natural Language Processing

AI Achievements - Natural Language Processing

AI Achievements - Natural Language Processing

A universal translator. Instant translation of any language to any other!

AI Achievements - Natural Language Processing

A universal translator. Instant translation of any language to any other!

AI Achievements - Natural Language Processing

A universal translator. Instant translation of any language to any other!

AI Achievements - Computer Vision

AI Achievements - Computer Vision

AI Achievements - Computer Vision

AI Achievements - Computer Vision

AI Achievements - Multi-agent Systems

AI Achievements - Vision + Actions + Planning +…

Source The Batch Newsletter.

AI Achievements - Vision + Actions + Planning +…

Source The Batch Newsletter.

AI Achievements - But how to put it all together?

AI Achievements - But how to put it all together?

Shakey

AI Achievements - But how to put it all together?

Shakey The Future?

References

Search

Klein, D., & Manning, C. D. (2003, May). A parsing: fast exact Viterbi parse selection. In Proceedings of

the 2003 Conference of the North American Chapter of the Association for Computational Linguistics

on Human Language Technology-Volume 1 (pp. 40-47). Association for Computational Linguistics.

Duchoň, F., Babinec, A., Kajan, M., Beňo, P., Florek, M., Fico, T., & Jurišica, L. (2014). Path planning with

modified a star algorithm for a mobile robot. Procedia Engineering, 96, 59-69.

Adversarial Search

Newborn, M. (2012). Kasparov versus Deep Blue: Computer chess comes of age. Springer Science &

Business Media.

Moravčík, M., Schmid, M., Burch, N., Lisý, V., Morrill, D., Bard, N., ... & Bowling, M. (2017). Deepstack:

Expert-level artificial intelligence in heads-up no-limit poker. Science, 356(6337), 508-513.

Silver, D., Schrittwieser, J., Simonyan, K., Antonoglou, I., Huang, A., Guez, A., ... & Chen, Y. (2017).

Mastering the game of go without human knowledge. nature, 550(7676), 354-359.

https://twitter.com/Kasparov63/status/1227391767584092160

References

Optimization

Davis, M., Logemann, G., & Loveland, D. (1962). A machine program for theorem-proving.

Communications of the ACM, 5(7), 394-397.

Gomes, C. P., Kautz, H., Sabharwal, A., & Selman, B. (2008). Satisfiability solvers.

Foundations of Artificial Intelligence, 3, 89-134.

https://satcompetition.github.io/2020/

Hidden Markov Models

Mamon, R. S., & Elliott, R. J. (Eds.). (2007). Hidden Markov models in finance (Vol. 4). New

York: Springer.

Sonnhammer, E. L., Von Heijne, G., & Krogh, A. (1998, July). A hidden Markov model for

predicting transmembrane helices in protein sequences. In Ismb (Vol. 6, pp. 175-182).

Rabiner, L. R. (1989). A tutorial on hidden Markov models and selected applications in

speech recognition. Proceedings of the IEEE, 77(2), 257-286.

References

Supervised Learning

Soni, J., Ansari, U., Sharma, D., & Soni, S. (2011). Predictive data mining for

medical diagnosis: An overview of heart disease prediction. International Journal

of Computer Applications, 17(8), 43-48.

Unsupervised Learning

Turney, P. D. (2002). Thumbs up or thumbs down? Semantic orientation applied

to unsupervised classification of reviews. arXiv preprint cs/0212032.

Oyelade, O. J., Oladipupo, O. O., & Obagbuwa, I. C. (2010). Application of k

Means Clustering algorithm for prediction of Students Academic Performance.

arXiv preprint arXiv:1002.2425.

Sculley, D. (2010, April). Web-scale k-means clustering. In Proceedings of the

19th international conference on World wide web (pp. 1177-1178).

References

Reinforcement Learning

Silver, D., Schrittwieser, J., Simonyan, K., Antonoglou, I., Huang, A., Guez, A., ... & Chen, Y.

(2017). Mastering the game of go without human knowledge. nature, 550(7676), 354-359.

Mnih, V., Kavukcuoglu, K., Silver, D., Graves, A., Antonoglou, I., Wierstra, D., & Riedmiller,

M. (2013). Playing atari with deep reinforcement learning. arXiv preprint arXiv:1312.5602.

Abbeel, P., Coates, A., Quigley, M., & Ng, A. Y. (2007). An application of reinforcement

learning to aerobatic helicopter flight. In Advances in neural information processing

systems (pp. 1-8).

Ipek, E., Mutlu, O., Martínez, J. F., & Caruana, R. (2008). Self-optimizing memory controllers:

A reinforcement learning approach. ACM SIGARCH Computer Architecture News, 36(3),

39-50.

Li, L., Chu, W., Langford, J., & Schapire, R. E. (2010, April). A contextual-bandit approach to

personalized news article recommendation. In Proceedings of the 19th international

conference on World wide web (pp. 661-670).

References

Multi-agent Systems

Kitano, H., & Tadokoro, S. (2001). Robocup rescue: A grand

challenge for multiagent and intelligent systems. AI magazine,

22(1), 39-39.

Image Credits

https://en.wikipedia.org/wiki/Google_Maps_pin

https://www.thehoneymoondestinations.com/best-flight-search-engines-sites-for-booking-cheap-

airfare/

https://www.deepstack.ai/

https://www.dailymail.co.uk/sciencetech/article-3950698/Why-toddlers-REALLY-love-play-hide-seek-

Young-brains-believe-really-invisible-hands.html

http://historyoflinearalgebra.weebly.com/andrey-markov-pdb.html

https://techcrunch.com/2018/05/14/you-can-now-try-smart-compose-in-the-new-gmail/

https://algorithmxlab.com/blog/computer-vision/

https://en.wikipedia.org/wiki/Tower_of_Babel

https://ph.news.yahoo.com/real-life-ai-rivals-star-wars-universal-translator-141610791.html

https://www.computerweekly.com/photostory/450423802/AI-A-brief-history-of-man-versus-machine-

intelliegnce/3/IBM-Watson-versus-Jeopardy

https://cosmosmagazine.com/technology/robocup-2017-wrap-up-highs-lows-plenty-of-falls/

https://frc.ri.cmu.edu/~hpm/project.archive/robot.papers/2000/revo.slides/1970.html

https://www.john-adams.nl/october-26-2014-soft-machines-deception/