What is the most preferred Artificial Intelligence System for Business Networking Improvement?

Mohamed-Mourad Lafifi

Dear Ylber,

I suggest you to see links and attached publicatins in subject.

-The 5 best programming languages for AI development | InfoWorld

https://www.infoworld.com/.../artificial-intelligence/the-5-best-pro...

-Artificial Intelligence Techniques Enhance Business Forecasts ...

https://gbr.pepperdine.edu/.../artificial-intelligence-techniques-enh...

-SDN + AI: A Powerful Combo for Better Networks | Light Reading

www.lightreading.com/...systems/sdn--ai-a...networks/d/.../725705

Best regards

Book Software engineering, artificial intelligence, networking an...

Conference Paper Artificial Intelligence Based Recommender Systems: A Survey

Conference Paper Privacy-Preserving Detection of Inter-Domain SDN Rules Overlaps

Mazin Abed Mohammed

Machine learning is enabling companies to expand their top-line growth and optimize processes while improving employee engagement and increasing customer satisfaction. Here are some concrete examples of how AI and machine learning are creating value in companies today:

1- Personalizing customer service. The potential to improve customer service while lowering costs makes this one of the most exciting areas of opportunity.

2- Improving customer loyalty and retention. Companies can mine customer actions, transactions, and social sentiment data to identify customers who are at high risk of leaving.

3- Hiring the right people. Corporate job openings pull in about 250 résumés apiece, and over half of surveyed recruiters say shortlisting qualified candidates is the most difficult part of their job.

4- Automating finance. AI can expedite “exception handling” in many financial processes.

5-Detecting fraud. The typical organization loses 5% of revenues each year to fraud. By building models based on historical transactions, social network information, and other external sources of data, machine learning algorithms can use pattern recognition to spot anomalies, exceptions, and outliers.

6- Smoother supply chains. Machine learning enables contextual analysis of logistics data to predict and mitigate supply chain risks.

Other areas where machine intelligence could soon be commonly used include:

7- Career planning. Recommendations could help employees choose career paths that lead to high performance, satisfaction, and retention.

8* Drone- and satellite-based asset management. Drones equipped with cameras can perform regular external inspections of commercial structures, like bridges or airplanes, with the images automatically analyzed to detect any new cracks or changes to surfaces.

9-Retail shelf analysis. A sports drink company could use machine intelligence, coupled with machine vision, to see whether its in-store displays are at the promised location, the shelves are properly stocked with products, and the product labels are facing outward.

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