Business finance - management business finance - management

Week2600.docx

Week 2 (no more than 200 words)

DISCUSSION PROMPT:

The Week 2 Lesson and Readings describe six (6) major subfields of AI. For this Discussion, select one of these six (6) subfields that interests you, and in your main discussion post, in your own words:

1. Identify the AI subfield you selected.

2. Describe an example of an AI application that uses this subfield, including a link to the example application.

3. Explain a way in which this AI application is disrupting a specific industry.

Machine learning (ML) is sometimes equated as a synonym of "AI," but that is a misnomer. ML is different.

ML is an application, or subfield, of AI involving the coding, processing, training, and evaluating of an AI model for utilization of data to produce predictive outcomes. The focus of ML is the development of algorithms and statistical models that enable computers to progressively improve their performance on a specific task as they are exposed to more data without being explicitly programmed for that specific task. Stated simply, "The machine learns. The model is programmed to learn on its own through its experience with the data. A major use of ML is in healthcare diagnostics" (Microsoft, 2024).

For examples of how this works, please read the following article: Seven Popular Applications of Machine Learning [article](this link opens in a new window/tab) .

Deep learning is the subfield of AI that teaches computers to process like the human brain to recognize complex patterns in pictures, text, sounds, and other data and analyze them to produce accurate insights and predictions. It is called "deep" because it functions in multi-layers, progressively refining unstructured data in a way that simulates the human brain (IBM, 2024). As mentioned above regarding the interrelationship of AI subfields, deep learning is integral in the functioning of the AI subfield of computer vision.

Examples of uses of deep learning include the following:

· Self-driving cars' reading of road signs

· Medical diagnostics in the reading of imaging

· Interpretation of satellite imaging

Week3Assignment600.docx

Week 3 Assignment: enterprise rental car private for-profit business

Prompt

Write an APA 7 formatted paper that incorporates the following information in a cohesive integrated paper. Do NOT present a "Q/A list."

Conduct factual research and select a real life currently operating private for-profit business OR NGO [article] that is using an AI application in its operations.

This can be a publicly-traded company, a private business, or NGO that you personally know or work for or one that you are interested in. It is important that you can research and obtain the information you need about the company to complete this assignment.

Content: Develop the following elements in your paper:

1. Name and describe the company; describe its industry and business. (Example: if you choose a grocery store chain business, the industry is retail. Name the company, and in describing the company, include its size, location(s), and so forth.)

2. Identify the AI application utilized by the company and its main subfield of AI. For example, is it NLP, deep learning, or another subfield of AI? (Likely more than one subfield will be involved. Identify the primary subfield. Refer to Week 2.) In non-technical terms, describe the AI application's function.

3. Describe the AI's operational role in your selected company.

4. Explain the benefits this AI application provides both the industry and your selected company in particular.

Format: Instructions:

1. Structure your paper according to APA Style 7th Edition guidelines. (Refer to APA Help materials in Classroom CONTENT/Overview.)

2. Use appropriate subheadings in organizing your paper. Follow the Word template attached to this Assignment. Also, The APA Sample Student Paper in APA Help shows you how to set up your subheadings.

3. Follow the Word template attached to this Assignment.

4. Length: 600–750 words (narrative text portion of paper). Do not include an abstract or other “extra” items—these will not count.

5. References: minimum of 3 credible sources.* All sources on the References list must also be cited in the paper as in text citations.

6. Be original, concise, and organized. Be sure to include all elements of the assignment.

Yu, D., Li, Z., Zhong, Q., Ai, Y., & Chen, W. (2020). Demand Management of Station-Based Car Sharing System Based on Deep Learning Forecasting. Journal of Advanced Transportation, 2020, 15. https://doi.org/10.1155/2020/8935857

Zhang, M., Xie, Y., Huang, L., & He, Z. (2014). Service quality evaluation of car rental industry in China. The International Journal of Quality & Reliability Management, 31(1), 82-102. https://doi.org/10.1108/IJQRM-11-2012-0146