Artificial intelligence which was born as a brain child of fiction writers is not a fiction anymore and has started its advent our daily lives, though not an integral part of our lives yet days are not far when our lives become easier with applications of AI.

The first thought that would come to our mind when we think of AI is a Robot, but Robot’s are just one of the multiple applications of AI, It’s true that in our future we will be having robots working all along with us simplifying all the tedious tasks but AI is not just about robots it’s about the system, that can act intelligently. Well this article is an attempt to present you a glimpse of our future based on the current research ongoing in the field of AI.

To give a non conventional introduction to AI, let me give this small example:

Given to a system that X is son of A also Y is son of A, the system must be able to say that X and Y are siblings. Yes, It’s the way of making system behave as humans, one of the hottest research going on is the develop a system that actually reason like human beings, researchers at the Rensselaer Polytechnic Institute have been successful to create a system which is able to reason as a 4-year-old child, it was named Eddie and its able to reason about his own beliefs to draw conclusions in a manner that matches human children of that age. The possible applications of this might be a virtual negotiator for a business company or a virtual online customer support, the user might be made to think that he is chatting with a human when he is actually chatting with an AI system and one thing we can learn here is the Turing test, which says that a system is said to be intelligent when an human judge is not able to reliably determine that the response is from a machine or human.

ALICE  : This video shows the latest evolved version of ALICE tested for turing’s test.

Applications of AI have grown. There are wide applications of developing a reasoning system , one day a system might become so intelligent that it might overtake man and build much more better systems that we cannot imagine!. Run Bot ,WIND The robot that can mimic human walking. ALICE , ELIZA This is AI system that can interact with human, it talks like a human being. Games, this is a no brainer… games use AI. Lace, an AI system to help people with cognitive disability. http://www.yourdiagnosis.com This is an online system developed , which uses AI to diagnose patients. http://witchit.com/ AI search engine, this searches based on contents instead of links. Inter Language search engines Search content in any language.  ASIMOV A famous humanoid robot, it can learn work and help in doing work. OmniZero, Robot and automobile! PARRO, Robot that nurse patients. Rice Planting Robot This can grow rice on it own.

RunBot Walking

Two things that scientists believed robots can never do is cycling and catching a ball as former requires balancing and the later requires dynamic judgment, but  the developments in robotics is showing all signs to disprove it. “RunBot” is a developed by Worgotter and his fellow researchers in Germany, the specialty of this bot is that it has an intelligence system designed to learn walking, the runbot can now not only walk mimicking human but can also climb higher terrains as ramps. This can be helpful for people with disability to regain their mobility, which can be a greatest gift to mankind. Engineers from Future Robotics Technology Center (fuRo), a division of the Chiba Institute of Technology, recently presented their latest invention Wireless Intelligent Networked Device (WIND), Device that allows a Robot to mimic a person’s moves.

AI in games

One of the most implemented form of AI is games, imagine a combat where a the opponent character learn your moves and try to avoid your attack the next time you do the same trick, or the difficulty of game increasing based on how successful you were in the previous round. This is possible with ai in games!

The web is now an integral part of our lives, and AI in web can change the way we use web, One thing that come to our mind when we think of web is Google, this is a search engine following Traditional Information Extraction (IE), it  takes a relation name and hand-tagged examples of that relation as input. Open IE is a relation independent extraction paradigm that is tailored to massive and heterogeneous corpora such as the Web. An Open IE system extracts a diverse set of relational tuples from text without any relation-specific input. With the application of AI Open IE can be a reality, with the efforts of M. Banko and O. Etzioni , A new model of Open IE has come to reality as TextRunner , this is a search engine for text content. You can try this at http://www.cs.washington.edu/research/textrunner. One more such search engine available is http://witchit.com/ this provides the content to user directly instead of providing link to web pages, this is really a great feature but is in initial stages of development and since this is based on machine learning it gets better day by day with its usage.

AI systems are also developed for the betterment of lives of people for whom there were no hopes or other solutions, one such system is LACE, The goal of the Laboratory for Assisted Cognition Environments (LACE) is to create advanced computer systems that will enhance the quality of life of people suffering from cognitive disabilities. This interdisciplinary project combines computer science research in artificial intelligence and ubiquitous computing with clinical research on patient care.  Assisted Cognition systems are proactive memory and problem solving aids that help an individual perform the tasks of day-to-day life.

AI has a lot of applications in the field of medicine. AIM : Artificial intelligence in medicine is a new discipline dealing with the issue, al lot of research is going on to develop a perfect “doctor in a box”, http://www.yourdiagnosis.com is an online doctor, which attempts to diagnose disease by asking various questions just like a doctor does also The Mayo Clinic is one such national integrated group of practice .

AI can be bought down to every single need of us and simplifying the most complex task, an example would be an application of library. Right now a digitalized library is a library where the book issue and search system is digital, think of a library where you can search for a topic you want to learn and you get list of books available with the given content, or the content with the same meaning as your search and in all languages that are in library! And yes this is possible with the application of AI.

Robots are sure to replace humans in many places of work, with the advent of Humanoid robots this is already becoming a reality, but it is somehow safer to use robots to very dangerous tasks performed by humans, tasks like mining where the workers are under extreme conditions of external environment really risk their life, it is also true that robots can perform many tasks better than human beings. With the application of AI like machine learning, we can have no doubts about robots outperforming humans. Japan, which can be considered as the capital of modern robots, sees its future in service robots. Economists predict that this helps Japan to re-emerge as the world top economic leader. ASIMOV a master piece by Japanese scientists is a humanoid robot which has a high level of communication and mobility skills is being used in posh business centers as a guide in their building to guide visitors of the building and to attract people. This has the capability to learn how to work based on the owners command. OmniZero is a Robot which can transform itself into car, wheel chair and also walk! PARO the furry robot. Robots are also used in Hospitals to help and nurse patients; PARO is once such robot which also got listed in Guinness book of records.One worth mentioning robot is Rice-Planting-Robot, which can sow and tend paddy all on its own.

Robo serving Food

We also have robots that can cook and also assist people in shopping by helping customers pick materials. Though all above mentions robots are developed by Japanese, it’s not a discouraging factor to others; it just shows the potential market to others and their opportunity for the future.

There are lot of areas where AI can be used, be it agriculture, design, banking, engineering, fraud detection, Law, tutoring systems, military, sports, telecommunication, scientific discovery etc. With the latest technologies that are emerging to build sophisticated robots powered with artificial intelligence is definitely going to create a revolution in the way we are living today. The future generation may look back at us and wonder how we were relying on a human doctor’s memory and experience or the man power we are wasting for the work that is obsolete to them.

Scientists speak on future of AI:

Having mentioned many of the advantages we shall also look at the problems that may arise due to use of robots, Of course nothing can beat the human brain as yet but the technologies developed right now if available to wrong hands can definitely cause a disaster. Imagine a spy robot with a camera which can follow any one anywhere which is now following you or a robot which can read persons mind based on neural activity in brain. But thank god such robots are not a reality yet though their prototypes and experiments are going on.

With all these said, let’s get ready for an intelligent future ahead!

Manu C
Student Content Intern

[ MSNBC ]

A solar-powered, remotely controlled robot roams the floor at the Robot Block Party at Stanford.

Photo by James Martin/CNET

[CNET]

AISight Features:

• Takes input from current and legacy cameras, recorded video or data files
• Recognizes, remembers and tracks objects frame by frame
• Rapidly learns what is acceptable behavior for any situation
• Identifies and predicts abnormal, suspicious and aggressive behavior
• Provides a wide range of alert systems to a human operator
• Requires no additional operator training
• Requires no changes to the existing infrastructure

About BRS Labs:

BRS Labs is a software development company that has created the industry’s first behavioral analysis system for video surveillance that adaptively learns behavior patterns in complex environments. BRS Labs is the only company that has been able to apply computer-vision and machine-learning capabilities to video analytics, thereby greatly enhancing operator awareness and effectiveness in improving security. No human is required to define parameters for the software to recognize behavior or objects; the software reports unusual or suspicious behaviors based on memories it has acquired through observations over time. BRS Labs was founded in November 2005 and is headquartered in Houston, Texas. The company is funded by $50 million in private equity.

[BRS Labs]

Now that you have watched the video, you can observe that,  Siri understands what you say, accomplishes tasks for you and adapts to your preferences over time. You can ask Siri questions naturally just as you will ask your assistant,like ” Book a ticket for London!” or ” Will it snow today?”. It understands information like where you are, what accounts you have on various services and the context of the last question you asked. Over time ,Siri will improve by getting to know you better and understand a broader set of tasks and soon you’ll trust it to manage many personal details in your life – from recommending a wine you might enjoy to managing your to do list.

The current version of Siri is built for iPhone 3GS and requires iPhone OS 3.1 or later. Soon, Siri will run on the iPod Touch, iPhone 3G and additional mobile platforms, as well.

Siri can get you information about Restaurants, Airline Tickets, Events, Taxis, Movies, Local and Weather Forcasts in a very simple conversation. Siri is the first Mobile Application which acts as a Virtual Personal Assistant. Its an intelligent software agent designed to have a back-and-forth conversational interaction with you as it helps you get tasks done.  The creation of Siri is a joint effort of designers and engineers pooled in from various all star organisations like Google, Yahoo, Apple, Motorola, Netscape, eBay, RealTravel, SRI, NASA, and Xerox PARC.

“In terms of long-term predictions, Siri is actually an easy bet.” – The New York Times.

“It’s the closest thing to a real assistant that you can talk to that I’ve ever seen.”- Vator News

To download this iPhone application visit :

http://siri.com/download/

For more details visit :

http://siri.com/

Photograph: The Korea Herald/Asia News Network

Currently, only 50 out of the total 8,300 kindergartens across the Korea use robots. The Ministry of Education plans to provide 800 robots to kindergartens in underprivileged parts of the country tin 2010. “We plan to provide robots to kindergartens in the rural areas and encourage others to voluntarily use robots. We expect all kindergartens nationwide to use robots by 2013.”- Ministry official.

The BEST part of this program is that the kids and teachers love the idea of robots in the class. Not only the robots aid the teacher in reducing the time spent on checking student attendance, or checking whether students are active  or not, but also the students enjoy communicate with the robots through the robots speech and voice technology. The ministry has designated the state-run Korea Institute of Science and Technology as a main organization handling matters related to the establishment of the system.

[ASIAONE]

Author: Randall Scott

Release Date: Jan 22, 2010

Website Release: Jan 22, 2010

Web page link: http://outskirtspress.com/webpage.php?ISBN=978-1-4327-4936-1

Email Contact: http://www.prlog.org/email-contact.html?id=10504152

Genre: COMPUTERS / Intelligence (AI) & Semantics

About the Author :-

Randall Scott is a retired Army Captain, Computer Scientist, and Assistant Professor. He holds a BS degree in Computer Engineering from Syracuse University and a MS degree in Computer Science (Software Engineering) from the Naval Postgraduate School.

Scott has served as a Tactical Communications Engineer, Systems Engineer, Software Security Expert, and much more. He lives in Martinez, Georgia.

About Outskirts Press, Inc. :-

Outskirts Press, Inc. offers full-service, custom self-publishing and book marketing services for authors seeking a cost-effective, fast, and flexible way to publish and distribute their books worldwide while retaining all their rights and full creative control. Available for authors globally at www.outskirtspress.com and located on the outskirts of Denver, Colorado, Outskirts Press represents the future of book publishing, today.

About the Book:-

A Guide to Artificial Intelligence with Visual Prolog by Randall Scott is available worldwide on book retailer websites such as Amazon and Barnes & Noble for a suggested retail price of $25.95.

ISBN: 9781432749361 Format: 6.14 x 9.21 paperback SRP: $25.95

Prolog – which stands for “programming with logic” -is one of the most effective languages with a unique approach for building AI applications . Using Prolog you define a problem with logical Rules, and then set the computer loose on it instead of writing a program that spells out exactly how to solve a problem. This paradigm shift from Procedural to Declarative programming makes Prolog ideal for applications involving AI, logic, language parsing, computational linguistics, and theorem-proving. Now, Visual Prolog (available as a free download) offers even more with its powerful Graphical User Interface (GUI), built-in Predicates, and rather large provided Program Foundation Class (PFC) libraries. A Guide to Artificial Intelligence with Visual Prolog is an excellent introduction to both Prolog and Visual Prolog. Designed for newcomers to Prolog with some conventional programming background (such as BASIC, C, C++, Pascal, etc.), Randall Scott proceeds along a logical, easy-to-grasp path as he explains the beginnings of Prolog, classic algorithms to get you started, and many of the unique features of Visual Prolog. Readers will also gain key insights into application development, application design, interface construction, troubleshooting, and more. In addition, there are numerous sample examples to learn from, copious illustrations and information on helpful resources. A Guide to Artificial Intelligence with Visual Prolog is less like a traditional textbook and more like a workshop where you can learn at your own pace – so you can start harnessing the power of Visual Prolog for whatever your mind can dream up. Deftly constructed at 190 pages, A Guide to Artificial Intelligence with Visual Prolog is being aggressively promoted to appropriate markets with a focus on the COMPUTERS / Intelligence (AI) & Semantics category. With U.S. wholesale distribution through Ingram and Baker & Taylor, and pervasive online availability through Amazon, Barnes & Noble and elsewhere, A Guide to Artificial Intelligence with Visual Prolog meets consumer demand through both retail and library markets with a suggested retail price of $25.95. Additionally, A Guide to Artificial Intelligence with Visual Prolog can be ordered by retailers or wholesalers for the maximum trade discount price set by the author in quantities of ten or more from the Outskirts Press wholesale online bookstore at www.outskirtspress.com/buybooks

For more information or to contact the author, visit www.outskirtspress.com/aguidetoartificialintelligence

This is a clear indication of what we can expect in the near future.(Oh boy! Not another American Robot idol, The Amazing robot race, America’s next top robot model, or robot factor)

Read more about the event here and for sure visit the compiled photo gallery1 and gallery2 for more pictures.

The robot hand is capable of 24 movements and can be remote-operated with the CyberGlove Photograph: Kim Kyung-hoon/Reuters

Humanoid industrial robot 'Motoman-SDA5D', developed by the Yaskawa Electric Corporation, demonstrates its capabilities with Lego Photograph: Dai Kurokawa/EPA

A humanoid robot 'Manoi AT01', produced by Japan's toy robot maker Kyosho, performs a hip-hop dance Photograph: Yoshikazu Tsuno/AFP/Getty Images

The University of Minnesota said Tuesday that it is one of the first academic partners to join the Planetary Skin Institute — a partnership between NASA and Cisco Systems Inc. that seeks to track global climate change.

The idea is to develop a global “nervous system” that will integrate land-, sea-, air- and space-based sensors. Software from University of Minnesota computer scientists will be part of the Planetary Skin prototype, set for 2010, that will track how much and where carbon is held by rain forests.

“We are excited to be an academic partner of Planetary Skin Institute,” Vipin Kumar, Researcher said. “This will allow us to greatly expedite the development and integration of advanced data-mining capabilities for the monitoring of the global ecosystem that is urgently needed in the context of climate change.”

Read more at the UM News.

Also on the other hand, A British university said Thursday it would investigate whether scientists at its prestigious Climatic Research Unit fudged data on global warming. This is a clear sign for the need of a standardized and unified approach  to solve our global climatic problems, even among scientific communities.

[1] Overview of AI, Agent Architectures : Video Lecture 1, Video Lecture 2

[2] Uninformed Search, Form teams : Video Lecture 3, Video Lecture 4

[3] Informed Search: Video Lecture 5

[4] Game Playing: Video Lecture 6

[5] Video Game AI, Logic: Video Lecture 8, Video Lecture 9

[6] Predicate Calculus, Inference: Video Lecture 10, Video Lecture 11

[7] Prolog Review: Video Lecture 12, Video Lecture 13

[8] Semantic Networks, Knowledge Representation: Video Lecture 14

[9] Uncertainty: Video Lecture 15, Video Lecture 16

[10] Intro Bayesian Networks, Intro Machine Learning: Video Lecture 17, Video Lecture 18

[11] Decision Trees: Video Lecture 19

[12] Neural Networks: Video Lecture 20, Video Lecture 21

[13] Genetic Algorithms, Information Retrieval: Video Lecture 22, Video Lecture 23

Natural Language Processing:

Lecture 1:

Topics:Logistics, Goals Of The Field Of NLP, Is The Problem Just Cycles?, Why NLP Is Difficult? The Hidden Structure Of Language, Why NLP Is Difficult: Newspaper Headlines, Machine Translation, Machine Translation History, Centauri/Arcturan Example

Video: Lecture 1.

Lecture 2:

Topics: Questions That Linguistics Should Answer, Machine Translation (MT), Probabilistic Language Models, Evaluation, Sparsity, Smoothing, How Much Mass To Withhold?

Video: Lecture 2

Lecture 3:

Topics: Finish Smoothing From Last Lecture, Kneser-Ney Smoothing, Practical Considerations, Machine Translation (Lecture 3), Tokenization (Or Segmentation), Statistical MT Systems, IBM Translation Models

Video: Lecture 3.

Lecture 4:

Topics: Review Statistical Mt, Model 1, The Em Algorithm, Em And Hidden Structure, Em Algorithm Demonstration In Excel Spreadsheet, Assignment 1

Video: Lecture 4.

Lecture 5:

Topics: IBM Model 1-2 (Review), IBM Model 3, IBM Model 4, IBM Model 5, Mt Evaluation, Bleu Evaluation Metric, A Complete Translation System, Flaws Of Word-Based Mt, Phrased-Based Stat-Mt

Video: Lecture 5.

Lecture 6:

Topics: Continue Of Machine Translation, Syntax-Based Model, Information Extraction & Named Entity Recognition, Information Extraction, Named Entity Extraction, Precision And Recall, Naive Bayes Classifiers

Video: Lecture 6.

Lecture 7:

Topics: Continue Of Naive Bayes Classifier, Joint V.S. Conditional Models, Features, Examples, Feature-Based Classifiers, Comparison To Naïve-Bayes, Building A Maxent Model

Video: Lecture 7.

Lecture 8:

Topics: Details Of Maxent Model, Maxent Examples, Convexity, Feature Interaction, Classification, Smoothing, Inference In Systems

Video: Lecture 8.

Lecture 9:

Topics: MEMM, Hmm Pos Tagging Model, Summary Of Tagging, NER, Information Extraction And Integration, Landscape Of IE Tasks, Machine Learning Methods, Relation Extraction, Clustering

Video: Lecture 9.

Lecture 10:

Topics: Parsing, Classical NLP Parsing, Two Views Of Linguistic Structure, Attachment Ambiguities, A Simple Prediction, What Is Parsing?, Top-Down Parsing, Bottom-Up Parsing, Parsing Of PCFGs

Video: Lecture 10

Lecture 11:

Topics: Chomsky Normal Form, Cocke-Kasami-Younger (CKY) Constituency Parsing, Extended CKY Parsing, Efficient CKY Parsing, Evaluating Parsing Accuracy, How Good Are PCFGs?, Improve PCFG Parsing Via Unlexicalized Parsing, Markovization

Video: Lecture 11.

Lecture 12:

Topics: Guest Lecturer: Dan Jurafsky, Syntactic Variations Versus Semantic Roles, Some Typical Semantic Roles, Two Solutions To The Difficulty Of Defining Semantic Roles, PropBank, FrameNet, Information Extraction Versus Semantic Role Labeling, Evaluation Measures, Parsing Algorithm, Combining Identification And Classification Models, Summary

Video: Lecture 12.

Lecture 13:

Topics: Lexicalized Parsing, Parsing Via Classification Decisions: Charniak (1997), Sparseness & The Penn Treebank, Complexity Of Lexicalized PCFG Parsing, Complexity Of Lexicalized PCFG Parsing, Overview Of Collins’ Model, Choice Of Heads, The Latest Parsing Results, Parsing And Search Algorithms

Video: Lecture 13.

Lecture 14:

Topics: Parsing As Search, Agenda-Based Parsing, What Can Go Wrong?, Search In Modern Lexicalized Statistical Parsers, Dependency Parsing, Naïve Recognition/Parsing, Discriminative Parsing, Discriminative Models

Video: Lecture 14.

Lecture 15:

Topics: Why Study Computational Semantics?, Precise Semantics. An Early Example: Chat-80, Programming Language Interpreter, Logic: Some Preliminaries, Compositional Semantics, A Simple DCG Grammar With Semantics, Augmented CFG Rules, Semantic Grammars

Video:  Lecture 15.

Lecture 16:

Topics: An Introduction To Formal Computational Semantics, Database/ Knowledgebase Interfaces, Typed Lambda Calculus, Types Of Major Syntactic Categories, Adjective And PP Modification, Why Things Get More Complex, Generalized Quantifiers, Representing Proper Nouns With Quantifiers, Questions With Answers!, How Could We Learn Such Representations?

Video: Lecture 16.

Lecture 17:

Topics: Lexical Semantics, Lexical Information And NL Applications, Polysemy Vs Homonymy, WordNet, Word Sense Disambiguation, Corpora Used For WSD Work, Evaluation, Lexical Acquisition, Vector-Based Lexical Semantics, Measures Of Semantic Similarity

Video: Lecture 17.

Lecture 18:

Topics: Question Answering Systems And Textual Inference, A Brief (Academic) History, Top Performing Systems, Answer Types In State-Of-The-Art QA Systems, Semantics And Reasoning For QA, The Textual Inference Task, Why We Need Sloppy Matching, QA Beyond TREC

Video: Lecture 18.

Note: If the links either expired or exhibit errors, please visit SEE program home page and navigate from there. Thanks.

Read Link compilation #4 here.