This you need to know about artificial intelligence (AI)
This is what one needs to know about artificial intelligence (AI) Intelligent agents taking over the world?
It is said that robotics and artificial intelligence are the future and that we will experience that many jobs disappear as a result. Examples mentioned are surgeons and factory workers. For the latter profession, we have already seen major changes, and therefore it is being discussed whether there may be an increased risk of fewer jobs in certain industries in the future. Automation thus seems threatening, and one wants everything to be as before.
See previous article: https://www.visualityglobal.com/l/is-your-job-secure-or-do-you-need-a-new-in-the-future/
This does not necessarily have to be the case. We need someone who can install, program, and build these robots.
Artificial intelligence (AI) and cognitive technology are becoming increasingly relevant to business.
Today we see that 4% of today's companies that use AI technology already. It is a rapidly growing market. In short, in recent years, the business community's interest in artificial intelligence (AI) has skyrocketed.
Venture capital companies invest billions in the development and commercialization of AI-related products and technologies, while established technology companies, such as Google, Facebook, and IBM, spend billions on the acquisition of AI start-ups.
Behind all communication in the media, we find significant commercial activity in the AI world. This will affect organizations in all industries and sectors. Business leaders should therefore understand what AI is and where technology leads.
See article: https://www.visualityglobal.com/l/only-4-have-started-using-artificial-intelligence/
What can AI be used for?
A distinction is made between artificial intelligence, as a general field and the specific technologies that come from the field. What is happening today is that the individual technologies are constantly getting better at carrying out tasks, which only humans were able to do. These technologies are called "cognitive technologies". Leaders in business and the public sector should turn their attention to cognitive technologies, and here are some of the most important.
Computer vision, or artificial vision, is about the ability of computers to identify objects, events, or activities in images. The technology uses image processing processes to deconstruct the image material, and then assesses whether the properties of the image can be linked to objects that the system already knows.
There are many different uses here, including face recognition, analysis in the field of health to strengthen prognoses, diagnoses and treatment of diseases, and shopping - where consumers can take pictures of products for more information.
Machine learning is the ability of a computer system to improve the performance of exposure to information, without the need to follow explicit programming instructions. The computer system automatically detects patterns in data and can then use the pattern to make estimates.
A machine learning system can, for example, be exposed to a database with information about card transactions, such as date, time, dealer, location, price and whether the transaction was legitimate or false. Through all the information, the machine learning system learns patterns that can predict frauds, and the more transaction data the system processes, the better the estimates. Machine learning has a wide range of applications, including sales forecasts, inventory management, oil and gas exploration, and public health.
Natural language processing
are about how computers can work with text the way humans do, such as extracting meaning or creating readable text that is grammatically correct. A natural language processing system can, among other things, identify people and places mentioned in a document, identify the topic, or extract terms and conditions in an easy-to-read presentation. Natural language processing uses several techniques: Language models can estimate the probability that certain combinations of characters and words are part of a language, while sample models can identify elements to distinguish one type of text from another - for example a junk e-mail from a legitimate email.
This is just a taste of what we're talking about when it comes to AI.
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Author Trond Paulsen