Artificial Intelligence

Agenda

Start End

Introduction

AI Future

Recent Developmen

ts

Turing Test

Turing Test Evaluation

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.

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

Turing Test

• Can Machines think?• “Can this machine consistently fool

users into believing it is human?”

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.

Turing Test Evaluation

• Strengths– Simple test– Wide array subject

matter• Weaknesses– The Chinese Room

Argument– Unintelligent

human behavior

ParsingAutomated parsing techniques were used on Arabic sentences, and achieved amazingly accurate results!

Speech

An artificial intelligence speech tool was built for the tonal Ibibio language.

Human speech Synthesized speech using context and tone labels

SpeechA 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

Translating

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

Text ExtractionCzech text was parsed to extract information.

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

The Future of AIOverview

• Uncertain• Trends in biologically inspired

techniques• Trends in statistical models with large

training data sets• Expanding into many other fields

Neuromorphic Chips

• IBM TrueNorth: 256 million synapses per chip

• Neuromorphic Engineering• Reverse engineering the brain

Semantic Search

Augmented Reality

Technological Singularity

Questions?