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The Foundations and History of Artificial Intelligence

Artificial Intelligence (AI) is the simulation of human behavior and cognition in a machine. This is not a new word and not a new technology for researchers. It has been observed that it was one of the oldest science on earth, even there are the myths of Mechanical men in Ancient Greek and Egyptian Myths. Now AI has evolved to be much more advanced and a lot of time is spent on research for making AI work on a high level. AI is not just about programs and computers but it’s a complex science that involves many different disciplines like computer science, math, statistics etc.

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How Would You Define Artificial Intelligence?

Artificial intelligence (AI), the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. Since the development of the Digital Computer in the 1940s, it has been demonstrated that computers can be programmed to carry out very complex tasks—as, for example, discovering proofs for mathematical theorems or playing Chess. Some claim that artificial intelligence is on the verge of becoming a reality in the form of "thinking machines". Still, despite continuing advances in computer processing speed and memory capacity, there are as yet no programs that can match human flexibility over wider domains or in tasks requiring much everyday knowledge. On the other hand, some programs have attained the performance levels of human experts and professionals in performing certain specific tasks, so that artificial intelligence in this limited sense is found in applications as diverse as medical diagnosis, computer search engines and voice or handwriting recognition.

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What Can Artificial Intelligence Offer Coral Reef Managers?

Artificial intelligence is an exciting technological frontier for the coral reef remote sensing community, especially the emergence of machine learning algorithms for mapping and detecting features from aerial images of coral reef environments. Machine learning algorithms are finding uses in environmental remote sensing applications that are principally founded on three technological advances: The spatial resolution of remote sensing images has increased incrementally since Earth Observation images were first collected in the late 1960s. Greater detail and smaller features are now visible in coral reef environments. Notably, the widespread use of drone platforms for collecting images at low altitudes above coral reefs has made individual corals visible. What this means is that AI algorithms can detect changes to the health of an ecosystem or determine if an area is being damaged; on the other hand, these algorithms can also help identify areas that are overgrown by coral colonies with ease. The “big data revolution,” refers to the phenomenon of increased capture of earth observation images, which has delivered the information on which artificial intelligence relies to recognize environmental patterns and trends. Global repositories are now continuously updated to provide real-time satellite images, often freely downloadable, for observing coral reefs. A wealth of image-based information is now available for training and evaluating algorithms to interpret coral reefs from above Credit for the first use of a computer for numerical calculation in radiology goes to Dr. Edwin H. Northrop of the Mayo Clinic, who in 1951 showed that computed tomography (CT) scans could detect lung cancer at the early stages of the disease. Since then, this technique has become essential to diagnosis, enabling many people with a variety of cancers to have surgery tailored specifically to their cases.

What Are the Impacts of Artificial Intelligence on the Creative Industries?

As the AI revolution continues, it has been widely predicted that the artistic domain will soon be completely overtaken by machines. In fact, there's already some solid evidence that creative industries such as music, advertising and even film are being transformed by AI—and not just in terms of how we interact with them but also in how they are derived from our interaction with them.

An exploration of the differences in marketing strategies across cultures

International Marketing is a strategic decision that involves developing a marketing mix strategy based on the characteristics of a potential foreign market. In simpler terms, it is how organizations should design and convey their messages if they want to sell their goods and services in a foreign market. Cultural differences can be very powerful in determining attitudes, beliefs, behaviour and attitudes towards brands, products and service which has significant impact on the performance of any organization trying to gain a foothold in international markets. International business is important to ensure that multinational companies expand their markets and penetrate new markets. Selling products in different countries requires different strategies. For example, if a company plans to sell its products in Australia, it must understand the cultural environment there before selling its product. Although the culture may be similar to other countries, there are still many differences in how they perform certain actions that can create great deal of difference when selling their products in these locales.

Agile Modeling, Agile Software Development, and Extreme Programming

While there are many claims for the successful use of extreme programming (XP) and agile modeling (AM), and the proponents can often be vocal in the extreme regarding their benefits, research evidence supporting these claims is lacking. Currently, the only research appearing to investigate the phenomenon consists of a small number of case studies and experience reports that promote the success of XP in development environments. The field of XP/Agile has seen tremendous growth since the early 2000s, and many people have begun using the practices in their organizations. However, very little research into XP/AM has been conducted. As such, there are few case studies to assist in understanding the practices. This article reviews existing research related to XP/Agile, recommending new areas that could benefit from further study. Since nearly all empirical XP research is on pairs programming, a closer look into other core practices would be beneficial. It might also be possible to group related concepts together for study purposes. Finally, much has been said about how XP can simply be repackaged or carried over from previous practice ideas which need further investigation.

Waterfall Project Management and Agile Project Management Comparison

Waterfall vs Agile Project Management Comparison.