Examples of Artificial Intelligence

Cleverbot is a chatterbot that’s modeled after human behavior and able to hold a conversation. It does so by remembering words from conversations. The responses are not programmed. Instead, it finds keywords or phrases that matches the input and searches through its saved conversations to find how it should respond to the input.
Alvin Mai

MySong is an application which can help people who has no experience in write a song or even can not play any instrument, to create original music by themselves. It will automatically choose chords to accompany the vocal melody that you have just inputed by microphone. In the other hand, MySong can help songwriters to record their new ideas and melodies no matter where and when they are. But MySong is not a professional application which can produce or edit your song, then it means you have to use other tools or software to really develop a song..
Yu Tang

atuomatic car contorl
First, it should have computer visoin, it can identify the car and people. Second, good control the car aviod the colliosn. And make the best plan to arrive the destination..
Ming Lei

Self-Repairing Hardware
Researchers at Caltech have made progress on an integrated circuit equipped with sensors and actuators that allow it to heal itself if it suffers any damage. The sensors read temperature, current, voltage, and power and the chip is given a goal state, such as maximum output power. The chip then modifies itself with its actuators and learns how close it is to its goal based on the readings from its sensors. Previous researchers (e.g. D. Mange et. al) have used evolutionary algorithms in the self-repair of programmable logic circuits. The field of embryonics (embryonic electronics) may also lead to hardware that can self-replicate as well as self-repair.
Bria Morgan

Flying drones
This flying drones use video cameras and sensors to translate the environment into a 3D model. There are also some cameras and sensors attached at the ceiling of the room, in order to detect the position of the drones in the room. Trajectory generation algorithm are used to instruct the drones how and where to move. Error calculation algorithm are used to determine a more precise position of a brick that the drone has to place. By a WIFI connection the drones are controlled by a computer, into which the model of the building is loaded initially, then instructed by the computer the drones construct the building.
Grigorii Lazari

IRobot Roomba is a machine that can do the vacuum cleaning by itself. The Roomba is able to detect how many room it need to clean which is Machine learning, and know what area it can clean which is automated reasoning, Also has the dirt detection which mean it will make sure all the dirt being cleaned which is computer vision. It has avoid the cliff sensing, anti-Tangle function and auto charge itself. Those function to ensure that the Roomba can clean by itself and charge it when it need it, All we need to do just setup the clean time and push the power button.
yipeng wu

video game bot
Video game bot is the easy way of using the Artificial Intelligence in real life. This application, wildly used in First Person Shooters (FPS), makes the players could play with the PC instead of human. The bot can attack the players and also could avoid the players’ attack. Bots could do something that program tell them and they could make their own choice by killing which player or bot first or choosing which way to go. Sometimes the human players even can not beat the bot, so we have to admit this video-game-bot application of AI is a great success.
Nian Zhang

Predicting Hydraulic Conductivity through AI Models
Researchers developed saturated hydraulic conductivity fields based on soil data through the use of three different AI models: radial basis function neural networks (RBFNN), multi layer perceptron neural networks (MLPNN), and adaptive neuro-fuzzy inference system (ANFIS). Existing data samples were divided into testing and training data. Based on testing data, ANFIS and RBFNN outperformed MLPNN and multiple linear regression at predicting hydraulic conductivity.
Karen Madsen

Natural Language Processing (NLP)
Initially Natural Language processing relied mostly on the Chomsky's theories of linguistics that included
generative grammars and universal grammars. Generative grammars provide a set of rules that can accurately
predict which combinations of words are able to make all of the possibly infinite grammatically correct sentences
of a language, and rule out all the ungrammatical sentences. Universal grammar as proposed by Chomsky on the
other hand suggests that all languages share common underlying principles which vary in systematic ways from
language to language.
Later on Machine learning algorithms for language processing were introduce.These algorithms are classified in
several caregories including Supervised learning (where the statistical classification belongs), Unsupervised
learning(where the association rule, Hierachical clusreing and partition clustering are, Reinforcement learning),
Reinforcement learning and many other groups of algorithms.
Daniel Musigire

Artificial Intelligence in Video Games
The AI components used in video games is often a slimmed down version of a true AI implementation, as the scope of a video game is often limited (ie Console memory capacity). The most innovative use of AI is garnered on Personal Computers, whose memory capabilities are adjustable beyond the capacity of modern gaming consoles.

Some examples of AI components typically used in video games are Path Finding, Adaptiveness (learning), perception, and planning (decision making).

The present state of video games can offer a variety of "worlds" for AI concepts to be tested in, such as a static or dynamic environment, deterministic or non-deterministic transitioning, and fully or partially known game worlds. The real-time performance constraint of AI in video game processing must also be considered, which is another contributing factor to why video games may choose to implement a "simple" AI, ie: finite state machine as AI, which may not even be considered Artifical Intelligence at heart.

Michael Bazzinotti

Artificial Intelligence in Mobile System
As smartphone come into our daily life, we need to the make our device even more clever. Recently, researchers are trying to apply traditional AI techniques into mobile environment. Those techniques, including speech recognition, machine learning, classification and natural language processing give us a more powerful application, such as SIRI on iOS, kinect from Microsoft. AI on mobile device introduces some new challenges, such as limited computation resource and energy consumption etc.
Ying Mao

Computer-Aided Diagnosis
Computer-Aided Diagnosis refers to the use of Artificial Intelligence to assist doctors with the interpretation of medical images. It is currently used in many hospitals to help diagnose breast, lung and colon cancer, and other diseases. Techniques of feature extraction and classification which have been developed in the field of Computer Vision are used.
Caitlin Kuhlman

Genetic Algorithm Traveling Salesman Problem with Javascript
This program using genetic algorithm to solve Traveling Salesman Problem. This is a NP-hard problem, which means we may never get perfect answer in limit time, however a good algorithm can approximate the perfect solution quickly. This program can generate many individuals(solutions) may have different genes and different to each other, then the stronger the individual is, which means the solution get better result, the probability of the gene it bearing will pass to next generation increase. Thus , after many generations, the distribution of genes will be stable and we can get a good, may not perfect, solution.
Siyuan Gong

autonomous car
The article I picked isn't so much on a single application of artificial intelligence, but more on one of the next big commercial goals that many companies are using A.I. to accomplish.The article describes the current capabilities of the Mercedes prototype and some of the safety features. There is also an explanation of the three levels of autonomous driving, in accords with the German auto industry consortium VDA (Verband der Automobilindustrie) and the German federal highway research institute (BASt). The article ends with some details on other companies that are also working on autonomous vehicles. I believe this is a important article because it discuses a branch artificial intelligence that will soon have a huge impact in everyday life.
Adrian Garay

Watson - IBM
Waston is an artificially intelligent application developed by IBM and used in different fields such as finance, engagement and healthcare to help users make their decisions. Waston is a Siri-like application in the idea of understanding the natural human language and come up with an answer; However, Waston store more than 200 million pages of data including the whole text of Wikipedia. In the healthcare field for example, Waston will suggests different types of treatment to doctors based on different criteria like medical history and hereditary history.
Thamer AlTuwaiyan

Applications of Artificial Intelligence to the Legal Profession
The use of artificial intelligence in the legal profession is an emerging area that is beginning to impact the practice of law and influence employment trends in the field. So far, most AI software for legal applications is intended for use during the discovery phase of the trial process, allowing tasks such as the review of large numbers of documents to be conducted by a few attorneys, rather than by the large teams of lawyers and paralegals traditionally required. Such "e-discovery" software leverages advances in areas such as natural language processing, knowledge representation, data mining, pattern detection, and social network analysis, among others. One company, Cataphora, develops technologies intended to detect conspiratorial behavior through analysis of employees' recorded communications. For example, their software reveals suspiciously deleted messages as unresolved nodes in graph representations of email exchanges.
Erik Young/td>

Game Playing
Minimax and Alpha-Beta pruning are two of the most important concepts of Game Playing. Minimax is a good example of the difference between long, complicated but naive coding and short , subtle algorithms. By following some steps, we can develop the computer player to the fastest way to win the game.While Alpha-Beta pruning helps to speed up the game twice. Additionally, from any position, our method should put the best move first.
Alaa Aljohani