How And Why Artificial Intelligence Raises Productive Efficiency
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Artificial Intelligence How Raises Productive Efficiency
Author: Johnny Ch Lok
language: en
Publisher: Independently Published
Release Date: 2020-11-06
⦁Can (AI) technology replace human labour nature of work to raise better productivity and efficiency? On technological innovation reason view point, the history development of artificial intelligence studying the intelligence is one of most ancient scientific discipline. The history development of artificial intelligence what aims to achieve human use to sense, learn remember and think, logic probability, decision making and calculation develop from mathematics, instead of replacement human labor functions.Artificial intelligence history development aim is the scientific analysis of skills in connection and practice with the appearance of computers from 1950 year beginning. The artificial intelligence (AI) can deal with the ultimate challenges. How can ( either biological or electronic) mind sense, understand and manipulate a world that is much simple and more complex than itself? And what if would human like to construct something with such capabilities? The general-purpose software of the early period of (AI) were only able to solve simple tasks effectively and failed when which should be used in a wider range or an more difficult tasks. One of the sources of difficulty was that early software had very few or mix knowledge about the problems which handled, and activities successes by simply syntactic manipulation. Moreover, the other difficulty was that many problems that were tried to solve by the (AI) were untreatable. The early (AI) software whether trying step sequences based on the basic facts about the problem that should be solved, experimented with different combinations till which found a solution. From the end the 1960 year, developing the so-called expert systems were emphasized. These systems had ( sue-based) knowledge base about the field which handled. Till to the beginning of the 1970 year, ( Prolog) the logical programming language was born, which was built in the computation realization of a version of the resolution calculus. ( Prolog) is a remarkably prevalent tool in developing expert systems ( on medical, judiciary and other scopes), but natural language parsers were implemented in this language. Then, in 1981 s, the Japanese announced the fifth generation computer system project, a 10 years plan to build an intelligent computer system that use the ( Prolog) language as a machine code. Nowadays, (AI) can be applied any industries, such as car manufacturing industry can use (AI) technological machine-men manufacture car, instead of replacing human labors in factory. Even, in the future, using (AI) machine-men drivers can drive any private cars or public transportation tools, instead of replacing human drivers, e.g. bus, train, tram, ferry etc. Also in the future, machine-men can replace housewives to serve families to do housekeeping clean job, e.g. cleaning toilets, bathrooms, kitchens, even cooking functions at home. So (AI) machine-man can reduce housewives works at home. Moreover, (AI) machine man can take care old people, when who are living at homes or elder care centers. So, it seems artificial intelligence (AI) will be possible developed to manufacture a new generation machine-man to assist ( serve) families to do any simply cleaning or cooking jobs at homes. Moreover, the overall demand of ( AI) general social needs will also rise, such as security, driving transportation tools, restaurant cleaning, elder centers care service etc. (AI) will have chance often to practise to do its tasks every day. It is possible that it can improve worker individual simple job duty to raise productivity and efficiency to be fast.
The Economics of Artificial Intelligence
Author: Ajay Agrawal
language: en
Publisher: University of Chicago Press
Release Date: 2024-03-14
A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.
How And Why Artificial Intelligence Raises Productive Efficiency And Service Performance?
Author: Johnny C. H. Lok
language: en
Publisher: Independently Published
Release Date: 2018-11-27
In the future, (AI) can be such a supervised learning machine man to supervise logistic workers and control and manage them how to deliver goods in warehouses more efficient. Even, they can replace human logistic workers to do their logistic tasks in warehouses. What is (AI) supervised learning system mean : It is learning that takes place when an (AI) -enabled system is directly informed by humans. I shall explain it as doctor case, A doctor who evaluates x-ray images to detect cancer risk, he/she can feed whose expert input images into an (AI) learning system to facilities supervised learning or when the (AI) learning system sorts through x-ray images for a doctor to review and approve in an effort to help improve the learning of the (AI) learning system. So, it seems that (AI) learning system can be applied to do any supervising tasks. When, (AI) robotic machines are applied to logistic warehouse environment, it can be one artificial intelligent supervisor to check any products whether are delivered to the exact locations or shelfs as well as the number of products whether it is accurate to be prepared to delivery to the outsider accurate destinations before all goods are already sent out from the warehouses. For example, Amazon publish company paper book buyers need to buy paper books , when they pay visa payment and every reader choose the right topic book from its website, when they choose to buy the topic of paper book, then Amazon publish will send the reader 's the topic book choice to its warehouse. When the logistic worker know what the topic of the paper book is sold, then the (AI) learning system will record the topic of the book and the country address of the paper book buyer to already to print the topic of paper book and send to the book buyer's address. Due to , there are many different countries paper book buyers who had chosen the different topic books to buy from amazon publish website. For example, if there are five hundred different countries book buyers who had paid visa to buy different topic books from Amazon publish website in the same day. Then , Amazon publish needs to deliver these five hundred different countries paper book buyers overseas address and the warehouse workers need to print all these five hundred different topic paper books in the same time in order to deliver all these five hundred paper books to their overseas home within two days. If Amazon publish has none of (AI) learning system to help it to record this five hundred different topic paper book buyers' overseas correct addresses and the accurate topic of every book. Then , I believe that Amazon publish has no more confidence to print the accurate different paper book right topic number and record all the different countries paper book buyers' overseas home addresses and names in order to print and deliver to them from warehouse within two days. SO, (AI) learning system can help this electronic publishing firm to record all these five hundred different countries paper book buyers' addresses and every paper book topic in its centered logistic system efficiently and effectively. Amazon publish can reduce some warehouse workers number , due to it has (AI) learning system to help it to record all paper book buyer's address and name and book topic clearly. Even, (AI) robotic machine men can help it to deliver any book to the accurate shelf location in order to delivery the right topic of every book to post to the right country's book buyer's address before all these five hundred different topic books are already posted to their overseas addresses by air planes.