Artificial intelligence (AI)
What is Artificial intelligence (AI),
Artificial intelligence (AI), also known as machine intelligence, is a branch of computer science that aims to imbue software with the ability to analyze its environment using either predetermined rules and search algorithms, or pattern recognizing machine learning models, and then make decisions based on those analyses. In this way, AI attempts to mimic biological intelligence to allow the software application or system to act with varying degrees of autonomy, thereby reducing manual human intervention for a wide range of functions. Artificial intelligence, or AI, is the use of computer science programming to imitate human thought and action by analyzing data and surroundings, solving or anticipating problems and learning or self-teaching to adapt to a variety of tasks
There are three main divisions of AI - neural networks, machine learning and deep learning. Neural networks (often called artificial neural networks, or ANN) essentially mimic biological neural networks by "modeling and processing nonlinear relationships between inputs and outputs in parallel." Machine learning generally uses statistics and data to help improve machine functions, while deep learning computes multi-layer neural networks for more advanced learning.
Artificial intelligence (AI) has come to define society today in ways we never anticipated. AI makes it possible for us to unlock our smart phones with our faces, ask our virtual assistants questions and receive vocalized answers, and have our unwanted emails filtered to a spam folder without ever having to address them.
The term "artificial intelligence" has many connotations, depending on the specific industry it is used in. Most often, however, “when people say 'artificial intelligence,' what they actually mean is machine learning," says Bethany Edmunds, associate dean and lead faculty in the computer science master’s program within the Khoury College of Computer Science. "[Although AI] is a large umbrella term that incorporates a lot of statistical methods, historically, what it actually means is a computer acting like a human."
The term "artificial intelligence" has many connotations, depending on the specific industry it is used in. Most often, however, “when people say 'artificial intelligence,' what they actually mean is machine learning," says Bethany Edmunds, associate dean and lead faculty in the computer science master’s program within the Khoury College of Computer Science. "[Although AI] is a large umbrella term that incorporates a lot of statistical methods, historically, what it actually means is a computer acting like a human."
What is the uses of AI
The overall research goal of artificial intelligence is to create technology that allows computers and machines to function in an intelligent manner. The general problem of simulating (or creating) intelligence has been broken down into sub-problems.
Its machine learning systems mine through hoards of data on the web and assess correlations between world events and their impact on asset prices. Information Extraction, part of artificial intelligence, is used to extract information from live news feed and to assist with investment decisions.
Career opportunity in AI
As the possible applications of AI continue to increase, so does the positive career potential for those with the skills needed to thrive in this industry. The World Economic Forum’s “The Future of Jobs 2018“ report predicts that there will be 58 million new jobs in artificial intelligence by 2022.
However, those with the necessary combination of skills are often hard to come by, Edmunds explains. “The job market is really huge in [AI], but a lot of people aren’t trained for it,” she says, resulting in an above-average job outlook for those who do have the skills needed to work in this niche area.
Read on to explore some of these top careers defining the industry today.
One of the most prominent examples of how user experience influenced technology we know today is Apple. The invention of Mac operating software—compared to Windows—came from the need for a product that was more user-friendly and which didn't require an advanced technical understanding to operate. Apple approached the development of the iPhone in the same way. "The iPhone was all about user experience," Edmunds says. "That was a [user experience expert] understanding how people interact [with their phones], including what's intuitive and what's not. Then they designed the best possible phone to fit those needs."
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