Machine learning is the concept of computer intelligence learning on its own through large amounts of data inputted by people. This form of technology is sometimes confused with artificial intelligence, which is also known as AI. AI is an advance form of machine learning capable of making intelligence decisions. An example of this would be Facebooks Alice and Bob AI Robots, which were able to create their own language. Sadly, Facebook shutdown these two AI robots because they created their own language without their creator’s knowledge. Furthermore, machine learning is a branch of artificial intelligence that is widely used throughout the world. Modern society is embedded with this intriguing technology. This exciting technology has …show more content…
To better describe this concept, an article from Software Technology states, “This is like giving a student a set of problems and their solutions and telling that student to figure [it] out …” (2016, Panos Louridas and Christof Eber). The way the computer learns is by grouping data together. This type of method uses two different types of grouping methods to help identify possible outcomes: classification and regression algorithms. Classification algorithms is the process of a computer relating a subject to a category. To best explain this concept, Stephen Marsland states “…consider a vending machine, where we use a neural network to learn to recognize different coins” (Machine Learning, Section 1.4). The computer learns by analyzing large amounts of data and then categorizing the data. This is how a computer system can identify a certain illness to assist medical staff identify a certain type of illness or disease. In addition, supervised learning can also utilize regression …show more content…
Machine learning first starts off with data which is then molded into an algorithm. The data needs to be accurate for the computer to predict trends. Within Mariette Awad and Rahul Khanna book, Efficient Learning Machines, they list the data processing steps of: collecting the data, processing the data, transforming the data into an algorithm, training the algorithm, testing the algorithm, applying the algorithm, and then executing the algorithm (Mariette Awad; Rahul Khanna). As Jason Bell states in his book, “you must come to accept that data will need to be cleaned and checked for quality before any processing takes place” (Jason Bell, page____). It’s obvious that all these skills require a degree of skills and intellect. This is why information technology salaries are lucrative within today’s job market. Many companies are eager to identify trends within their customer base that could lead to massive amounts of profits. With this in mind, machine learning has allowed some major breakthroughs within
Computers, like us, need to be taught something. It is necessary to provide the computer with the data needed to learn. Despite the fact that they can run through the data several times quicker than a human, it takes a computer an incredibly long time to learn and is one sided. They are usually capable of knowing how to do one specific task, but at an extreme level. However, with increases to computer speeds and improvements to the code, computers are learning at faster speeds than the first artificial
Who would have guessed that the once mere concept of artificial intelligence (AI) could actually be a reality in the year 2015? Artificial intelligence is the intelligence exhibited by machines or software. It is also the name of the academic field of study which studies how to create computers and computer software that are capable of intelligent behavior. But we can go even deeper into the topic and question: really what defines intelligence? In this day and age if you were to ask a child this question I’m sure it was greatly differ from a child’s answer thirty, twenty or even ten years ago. The technological world is ever-changing, growing exponentially and very quickly and this is causing extreme effects on the lives of every person on
Artificial Intelligence (AI) is one of the newest fields in Science and Engineering. Work started in earnest soon after World War II, and the name itself was coined in 1956 by John McCarthy. Artificial Intelligence is an art of creating machines that perform functions that require intelligence when performed by people [Kurzweil, 1990]. It encompasses a huge variety of subfields, ranging from general (learning and perception) to the specific, such as playing chess, proving mathematical theorems, writing poetry, driving a car on the crowded street, and diagnosing diseases. Artificial Intelligence is relevant to any intellectual task; it is truly a Universal field. In future, intelligent machines will replace or enhance human’s capabilities in
Data mining is process of computing the data from the large data sets involving methods on to intersection of statistics, machine learning,
Data mining is the technique to interpret the data from other perspective and summarize the data so that the data can be useful information. Technically, data mining is a process to identify relations or patterns in the databases to predict the likelihood of future events. According to Eliason et al, there are three systems for healthcare organization to implement the mining data systems. The three systems are the analytics system, the content system and the deployment system. The analytics system is a system that used to collect all data such as patients clinical data, patients financial data, patients satisfactory data and other data. The content system is used to store all medical evidenced data. The deployment system is used to make new organization structure. There are several elements that consist in data mining which are first extract, transform and load transaction data onto the data warehouse system, second, store and manage the data in a multidimensional system, third, provide data access to information technology professionals, forth, analyze the data by application software and lastly, present the data in graph or table format.
Artificial intelligence or "AI" is the study of computer science that tries to enlighten and to imitate, through machine-driven or computational procedures, facets of human intelligence. Incorporated amid these aspects of intelligence are abilities to intermingle with the natural world across sensory methods and decision making abilities in unpredictable situations without human interference. Standard areas of exploration in AI consist of computer vision, game playing, learning, natural language understanding and synthesis, as well as problem solving and robotics (Noreen Herzfeld, 2003).
Clustering algorithms are used to discover structures and groups in the data, e.g. it classifies the data belongs to which group
...and Eclat. The classification is based on the features such as the technique, memory utilization, database and time of each individual algorithm. The essential information of all the algorithms is clearly summarized in Table 6, discussed in the paper.
Artificial intelligence can generate various types of disadvantages. Although AI has created many workforce opportunities, it has also resulted the automation of most of the basic activities which will lead to the reduction of human activities, jobs and tasks. For example, an AI software called e-discovery was developed that replaced lawyers, this software is able to analyze millions of documents and able to discover the facts fast and efficiently. This issue will result in many job losses which will lead to some social and ethical dilemma as when unemployment occurs unethical activities like stealing will occur in order to have the ability to
Artificial intelligence was the most popular phenomenon of the decade of 1950s. Since then, there has been much debate about its impact on society especially in terms of human dignity, unemployment, and environmental damage.
According to the website Science Fiction and Fantasy World, artificial intelligence (A.I.) can be defined as "the simulation of human intelligence processes by machines, especially computer systems." (Moy, par. 2) This domain has predominantly been a field characterized by complex research in laboratory scale environments and just only recently has been becoming a part of the scene of technology in commercial applications. A.I. is about to become a real force in our technological evolution. There has been so much development and change in the last ten years that it is hard to believe how far we have come. But there is going to be another technical revolution going on, and it will be about A.I.
Abstract: The number of video games involving human computer interaction have increased significantly. When a user interacts with a machine through an interface, a feedback is generated which is either displayed as output or stored for further processing. Decision making by machines can involve large number of computations and simulations so that the computer's move is beneficent to its own game. This paper provides definitions of major areas of Artificial Intelligence and Computational Intelligence in gaming. Chess is an example of such a high level application of artificial and computational intelligence. Chess engines evaluate current position of the chess board and decide which the next best move is. Various approaches towards computing
Humans can expand their knowledge to adapt the changing environment. To do that they must “learn”. Learning can be simply defined as the acquisition of knowledge or skills through study, experience, or being taught. Although learning is an easy task for most of the people, to acquire new knowledge or skills from data is too hard and complicated for machines. Moreover, the intelligence level of a machine is directly relevant to its learning capability. The study of machine learning tries to deal with this complicated task. In other words, machine learning is the branch of artificial intelligence that tries to find an answer to this question: how to make computer learn?
The major focus of machine learning research is to extract information from data automatically, by computational and statistical methods. Machine learning is closely related not only to data mining and statistics, but also theoretical computer science. Machine learning has a wide spectrum of applications including natural language processing, syntactic pattern recognition, search engines, medical diagnosis, brain-machine interfaces and cheminformatics, detecting credit card fraud, stock market analysis, speech and handwriting recognition, object recognition in computer vision, game playing and robot locomotion [1].
Being an “expert” means having a special knowledge or ability that allows you to perform actions skillfully, and at a higher level of confidence. It means having an extensive and task-specific skill learned from training, doing, and flat out experience. Knowing the facts, theories, and procedures about a general problem area is defined as being skilled in that area. A new subset of artificial intelligence was created with the definition of expert in mind. Early work with artificial intelligence was focusing too much on methods of search and heuristics which limited the search for solving problems. With much success, in 1978 some remarkable people at Stanford University designed a system called DENDRAL. It uses a chemist’s knowledge to find out what a chemical substance is. This was the birth of what we now call an “Expert System”.