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1 Introduction1.1 Purpose of the ReportThe purpose of this report is to educate the audience on the advancement and technology of modern day artificial intelligence and robotics. The paper will go through the various subtopics and different types of artificial intelligence as well as how different companies and organizations use them. Those interested in acquiring data and examples on the different types of AI solutions will find this paper useful as well as those looking for examples on the subject matter. The intended audience for the paper would be students or researchers of all types looking for information on AI and robotics. The content covered is broad and vague meaning that anyone can understand the content in the report1.2 Background of the ReportArtificial intelligence is intelligence displayed by machines, in contrast to natural intelligence displayed by humans and other animals. The term “Artificial intelligence” is applied when a machine mimics “Cognitive” functions that humans associate with other human minds, such as “Learning” and “Problem solving”. The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring “Intelligence” are often removed from the definition, a phenomenon known as the AI effect, leading to the phrase “AI is whatever hasn’t been done yet.” For instance, optical character recognition is frequently excluded from “Artificial intelligence”, having become a routine technology. Capabilities generally classified as AI as of 2017 include successfully understanding human speech, competing at a high level in strategic game systems, autonomous cars, intelligent routing in content delivery networks, military simulations, and interpreting complex data, including images and videos. Artificial intelligence was founded as an academic discipline in 1956, and in the years since has experienced several waves of optimism, followed by disappointment and the loss of funding,followed by new approaches, success and renewed funding. General intelligence is among the field’s long-term goals. Approaches include statistical methods, computational intelligence, and traditional symbolic AI. Many tools are used in AI, including versions of search and mathematical optimization, neural networks and methods based on statistics, probability and economics. The AI field draws upon computer science, mathematics, psychology, linguistics, philosophy, neuroscience, artificial psychology and many others. Examples of these will be touched upon later on but most detail on how these thing work will be omitted.2 Goals of Artificial Intelligence2.1 AlgorithmsAn algorithm is a process or set of rules to be followed in calculations or other problem-solving operations by a computer. Typically, the computer will run through the given data and find the most efficient method of solving the problem supplied. The computer usually won’t stop until the desired outcome is reached. Early researchers developed algorithms that imitated step-by-step reasoning that humans use when they solve puzzles or make logical deductions. By the late 1980s and 1990s, AI research had developed methods for dealing with uncertain or incomplete information, employing concepts from probability and economicsRubik’s cubes for example, have the problem of having its colors mismatched where the goal of the user is to place all the colors on the appropriate side. Whether it is apparent or not, algorithms, or patterns, are                       Fig 1.used to solve the rubik’s cube. That is, with enough uses of the different rubik’s cube patterns, the whole puzzle can be solved. Figure 1 shows patterns, or for a computer, algorithms used to solve different problems on the cube.2.2 Natural Language ProcessingNatural language processing gives machines the ability to read and understand human language. AI may interpret language in many ways like reading internet articles or holding conversation with other users on the internet where the knowledge of who you may be talking to is unknown. Other methods of displaying artificial intelligence through natural language processing includes chats bots like cleverbot. Cleverbot learns how to talk to people by having conversation data constantly streamed for cleverbot to see, for an example. Often times bots like Siri by Apple are mistaken as AI when really Siri has been designed with preset responses to questions designed to be asked for it. In the case that you say something that Siri wasn’t designed to answer, it points you to a google search instead.2.3 PerceptionThe Goal of of perception in AI is help people work with the world around them in a way otherwise impossible. Artificial intelligence can intelligently interpret data from video footage to understand an environment that it is in and make the decision that is needed.With facial recognition, AI hopes to learn how to identify and verify people and compare them to what is held in a database. Traditional methods see that inventoried faces are compared to landmark facial features through the use of algorithms. Object Outline Recognition technology belongs to the field of computer vision for finding and identifying objects in an image or video sequence. Humans recognize a multitude of objects in images with little effort, despite the fact that the image of the objects may vary somewhat in different viewpoints, in many different sizes and scales or even when they are translated or rotated. Objects can even be recognized when they are partially obstructed from view. This task is still a challenge for computer vision systems. Many approaches to the task have been implemented over multiple decades including edge comparison methods, changes in light, viewing direction, and shapes, or recognition by parts. 2.4 Motion and manipulation: RoboticsGreat strides have been achieved in the field of robotics and most examples of this are already being experimented with. The field of robotics is closely related to AI. Intelligence is required for robots to handle tasks such as object manipulation and navigation, with sub-problems such as localization, mapping, and motion planning. These systems require that a robot is able to be spatially aware of its surroundings, learn from and build a map of its environment, figure out how to get from one point in space to another, and execute that movement. Leaders in the industry of robotics are hoping that their products will be able to help those in need, be it military, professional, or home use.2.4 CreativityBeing able to output useful and novel creations, especially while staying comparable to human creation, is another goal of AI and robotics. Creativity in artificial intelligence is important not because it is specifically useful but because it goes to measure how well AI can perform at a task. AI platforms like Google’s Deep Dream. The goal of Deep Dream is to show how neural networks can work and to explore the capabilities of AI. 3 Applications of Artificial Intelligence3.1 Healthcare AI plays an important role in healthcare and will be watch closely as AI develops. Autonomous surgery and medicine prescriptions done by AI are becoming increasingly popular. Microsoft is working on a project to develop a machine called “Hanover”. Its goal is to memorize all the papers necessary to cancer and help predict which combinations of drugs will be most effective for each patient. One project that is being worked on at the moment is fighting myeloid leukemia, a fatal cancer where the treatment has not improved in decades. Another study was reported to have found that artificial intelligence was as good as trained doctors in identifying skin cancers.3.2 AutomotiveAdvancements in AI have contributed to the growth of the automotive industry through the creation of self-driving vehicles. As of 2016, there are over 30 companies utilizing AI into the creation of driverless cars. A few companies involved with AI include Tesla, Google, and Apple. Many components contribute to the functioning of self-driving cars. These vehicles incorporate systems such as braking, lane changing, collision prevention, navigation and mapping. Fig. 2Recent developments in autonomous automobiles have made the innovation of self-driving trucks possible. The UK government has passed legislation to begin testing of self-driving truck platoons in 2018. Self-driving truck platoons are a fleet of self-driving trucks following the lead of one non-self-driving truck, so the truck platoons aren’t entirely autonomous yet. Meanwhile, the Daimler, a German automobile corporation, is testing the Freightliner Inspiration which is a semi-autonomous truck that will only be used on the highway.3.3 EconomicsFinancial institutions have long used artificial neural network systems to detect charges or claims outside of the norm, flagging these for human investigation. The use of AI in banking can be traced back to 1987 when Security Pacific National Bank in USA set-up a Fraud Prevention Task force to counter the unauthorised use of debit cards. Programs like Kasisto and Moneystream are using AI in financial services.Banks use artificial intelligence systems today to organize operations, maintain book-keeping, invest in stocks, and manage properties. AI can react to changes overnight or when business is not taking place. In August 2001, robots beat humans in a simulated financial trading competition. AI has also reduced fraud and financial crimes by monitoring behavioral patterns of users for any abnormal changes or anomalies.3.4 Video GamesArtificial intelligence is used to generate intelligent behaviors primarily in non-player characters, often simulating human-like intelligence.

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