2. Randomness and creativity. After 60 years, results

2.

Problem definition:How can artificial intelligence be employed to increase the efficiency andeffectiveness in purchasing and supply chain management?3. Current research on the topicThe official idea and definition of Artificial Intelligence was first coined byJohn McCarthy in 1955 at the Dartmouth Conference. According to Mr. JohnMcCarthy “Every aspect of learning or any other feature of intelligence can inprinciple be so precisely described that a machine can be made to simulate it.An attempt will be made to find how to make machines use language, formabstractions and concepts, solve kinds of problems now reserved for humans, andimprove themselves”.In essence, artificial intelligence is a machine with the ability to solveproblems that are currently done by humans with their natural intelligence. Acomputer will demonstrate a form of intelligence when it learns how to improveitself as solving these problems.

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The 1955 proposal defines 7 areas of A.I.:1. simulating higher functions of the human brain.2. Programming a computer to use general language.3.

Arranging hypothetical neurons in a manner so that they can form concepts.4. A way to determine and measure problem complexity.5. Self-improvement6. Abstraction: Defined as the quality of dealing with ideas rather thanevents.7.

Randomness and creativity.After 60 years, results have been achieved in language, measuring problemcomplexity and self-improvement. Randomness and creativity are just starting tobe explored in detail.In the definition of the idea the word intelligence is mentioned. According toMr. Jack Copeland, who has written several books on A.

I. some of the mostimportant factors of intelligence are: generalization learning – learning thatenables the learner to be able to perform better in situations not previouslyencountered, reasoning- the ability to draw conclusions appropriate to thesituation at hand, problem solving – given such and such data find x,perception – analyzing a scanned environment and analyzing features andrelationships between objects as example self-driving cars, languageunderstanding, understanding language by following sintax and other rulessimilar to a humanExamples of A.I. are machine learning, computer vision, natural languageprocessing, robotics, pattern recognition and knowledge managementThere are also different types of artificial intelligence in terms of approach:Strong A.I.

and weak A.IStrong A.I. is simulating the human brain by building systems that think and inthe process give us an insight into how the brain works. In theory, It can doanything as well/better than a human brain, but the current technological stageis not near in achieving thisWeak A.I. is a system that behaves like a human but doesn’t give an insightinto how the human brain works, IBM’s Deep Blue, a chess playing A.I.

is anexample: it processed millions of moves before it made any actual moves on thechessboard. Also there is a middle ground between strong and weak A.I. This iswhere a system is inspired by human reasoning but doesn’t have to stick to it.IBM’s Watson is an example, like humans it reads a lot of information, recognizespatterns and builds up evidence to say ” I am x percent confident that this isthe right solution to the question that you’ve asked me from the informationthat I have read.Google’s deep learning is similar as it mimics the structure of the humanbrain, by using neural networks: ths system uses nodes that act as artificialneurons connecting information, going deeper neural networks are a subset ofmachine learning. Machine learning referes to algorithms that enable softwareto improve its performance over time as it obtaines more data. This isprograming by input output examples rather than coding.

As example: aprogrammer would have no idea how to program a computer to recognize a dog buthe can create a program with a form of intelligence that can learn to do so, ifhe gives the program enough image data in the form of dogs and let it processand learn, when you give the program an image of a new dog that is never seenbefore it would be able to tell that is a dog with relative ease.The last concept on artificial intelligence: most artificial intelligencealgorithms are expert systems. An expert system is a system that employs humanknowledge in a computer to solve problems that ordinarily require humanexpertise. Basically represents the practical application of a knowledgedatabase. In summary, artificial intelligence can help to address some of the society’stoughest and most pressing problems, from climate modeling to complex diseaseanalysis.

We’re excited to see what we can use this technology to tackle first,as mentioned y Demius hasibus, the co-creator of Deepmind. AI can be used for the products that are classified as “tail-end spend”. AI canreceive information on past quotes what each individual seller can offer as discountor price reduction, what are the minimum characteristics, factors andrequirements of each product and.4. Central question of the thesisHow can artificial intelligence help reduce costs and increase efficiency andeffectiveness of the corporate purchasing and supply chain management?5. Knowledge interest of the author6. The research objective and/or the underlying hypothesisWhat actions do procurement and supply chain leaders to implement artificialintelligence in their organizations?7.

Which methods lend themselves to work on the central question/hypothesis (theoreticalvs empirical, primary vs secondary analysis, qualitative vs quantitative, or acombination of methods etc.)8. Sources

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