Artificial Intelligence is opening up innovative prospects

Artificial intelligence must have access to objects, categories, properties and relations between all of them to implement knowledge engineering.

ARTIFICIAL intelligence is a branch of computer science that aims to create intelligent machines. It has become an essential part of the technology industry. Artificial Intelligence is a massively powerful tool that comes with a great deal of responsibility. As society changes to accommodate an all-machine service world, it also opens up new jobs for the next generation, such as writing software, repairing and maintaining robots, and developing new and better systems. Notably, machines are also primed to take over dangerous jobs.
Indeed firefighting, mining, deep-sea oil drilling, construction, and other careers with high mortality rates will be replaced by machines that can’t get sick or hurt. Economists believe that the world might be a brighter and more rewarding place with machines taking over the more dull and hazardous jobs.
Knowledge engineering is a core part of AI research. Machines can often act and react like humans only if they have abundant information relating to the world. Artificial intelligence must have access to objects, categories, properties and relations between all of them to implement knowledge engineering. Initiating common sense, reasoning and problem-solving power in machines is a difficult and tedious task.

Machine learning is also a core part of AI. Learning without any kind of supervision requires an ability to identify patterns in streams of inputs, whereas learning with adequate supervision involves classification and numerical regressions. Classification determines the category an object belongs to and regression deals with obtaining a set of numerical input or output examples, thereby discovering functions enabling the generation of suitable outputs from respective inputs. Mathematical analysis of machine learning algorithms and their performance is a well-defined branch of theoretical computer science often referred to as computational learning theory.
Capability to use sensory inputs
Machine perception deals with the capability to use sensory inputs to deduce the different aspects of the world, while computer vision is the power to analyze visual inputs with a few sub-problems such as facial, object and gesture recognition.
Robotics is also a major field related to AI. Robots require intelligence to handle tasks such as object manipulation and navigation, along with sub-problems of localization, motion planning and mapping.
Algorithms that can monitor and process massive amounts of data, and make conclusions based on patterns in that data are poised to change every avenue of society. Starting from something small — optimizing traffic patterns over time to figure out the best routes to take, or how to fix roads and rebuild highways — to something much more serious, like monitoring epidemics and diseases, and stopping them before they spread.
Artificial intelligence (AI) has the potential to offer $15.7 trillion to the global economy by 2030. You already encounter it every day. Think of all those times Amazon recommended a book to you or Netflix suggested a film or TV show. Those recommendations are based on algorithms that examine what you’ve bought or watched. The algorithms learn from those purchases, using them to suggest other things you might enjoy. Artificial intelligence lies behind those algorithms.
Simple artificial intelligence even filters your incoming emails, diverting spam away from your inbox. It works better than software rules because it learns what could be spam based on the content of the email. The artificial intelligence even builds a model based on your preferences—what is spam to you may not be spam to another user.
Artificial intelligence goes so much further than recommending a book or filtering your emails. Let’s take a look at the other ways we can measure the impact of artificial intelligence in everyday life.
How often do you ask Siri or Cortana a question? Do you order an Uber through Alexa or plan appointments using the Google Assistant? Each time, you’re interacting with artificial intelligence.
The most commonly advertised AI job at the moment is software engineer, which represents about 8.48 percent of the total. This is followed by data scientist and, perhaps not surprisingly, interns, since many firms undoubtedly want to skill up younger employees in the ways of AI. Other top positions include intelligence specialist, data analyst and both sales and product engineer.
12,000+ AI-related positions in China
Regionally, the biggest demand for all AI-related skills will be in China, with an estimated 12,000+ positions in the offering, followed by the United States at nearly 7,500, mostly concentrated in the technology hubs in California, Washington, Virginia, Massachusetts and New York.
But what about those in non-technical roles, or even technical jobs that lend themselves to hands-on, rote management functions? Sadly, most of these will fade way, says venture capitalist Sam Altman, but the good news is economic activity could jump by 50 percent or more, which means that even with AI there probably won’t be enough people to fill all the new jobs being created. And since these jobs will require high degrees of intuition and creativity, attributes that AI is not likely to acquire any time soon, tomorrow’s jobs will be more lucrative and personally fulfilling.
“Entire classes of jobs will go away and not come back. There’s a lot of things we have to figure out – how people find meaning, community, but a lack of material abundance will not be a problem.”
— Internet

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