1. Artificial Intelligence

2. Agenda StartEnd Introduction AI Future Recent Developments Turing Test Turing Test Evaluation

3. Introduction Artificial intelligence (AI) The science and engineering of making intelligent machines (John McCarthy, 1956) The study and design of intelligent agents/systems (Science Daily) AI Uses insights from many fields (computer science, psychology, linguistics, economics, etc.) Relevant to robotics development, facial recognition software, speech recognition software, etc.

4. Turing Test Created by Alan Turing in 1951 Began as a game to see if a judge could tell the difference between a computer and a human Now the goal is to develop software/programs that can accurately process human language and generate appropriate responses Loebner prize offered every year; No winners yet

5. Turing Test Can Machines think? “Can this machine consistently fool users into believing it is human?”

6. Turing Test June 7, 2014, University of Reading Eugene Goostman, a chatbot 33% of judges fooled Controversial: Chatbot pretended to be young with poor English skills. Dodged questions rather than answering.

7. Turing Test Evaluation Strengths – Simple test – Wide array subject matter Weaknesses – The Chinese Room Argument – Unintelligent human behavior

8. Parsing Automated parsing techniques were used on Arabic sentences, and achieved amazingly accurate results!

9. Speech An artificial intelligence speech tool was built for the tonal Ibibio language. Human speechSynthesized speech using context and tone labels

10. Speech A dictation tool was constructed for Slovak speech, which achieved great performance using this model. sounds of the sentence the darker the RED arrow, the more likely the pointed number is to be the next word words the darker the BLACK arrow, the more likely the word is to correspond to a sound

11. Translating A written system was developed to first capture Polish sign language, then translate it.

12. Text Extraction Czech text was parsed to extract information.

13. Text Extraction Sample tests were given to evaluate the effectiveness of such algorithms, and accomplished decent accuracy.

14. The Future of AI Overview Uncertain Trends in biologically inspired techniques Trends in statistical models with large training data sets Expanding into many other fields

15. Neuromorphic Chips IBM TrueNorth: 256 million synapses per chip Neuromorphic Engineering Reverse engineering the brain

16. Semantic Search

17. Augmented Reality

18. Technological Singularity

19. Questions?