” Break the Fields into Divisions for Applications in ChatGPT – Management and Industrial Engineering Perspective – February 7, 2023.

ChatGPT has reinvigorated the concept of avant-garde beyond a revolutionary style in the growth of Technology. Answering questions ; writing essays, speeches, and articles ; compare and contrast opinions and philosophies held by individuals ; and even writing software codes – captivating and engaging not just specialists in education/industry but everyone from GenZers to Baby boomers with no distinction. Pros and cons are being debated. Memories of growth come galloping forward and backward.

ChatGPT can be taken to have crossed the introductory innovation stage and entered the growth/application stage now. The challenge now is to expand its growth in as many sectors as possible with the benefits reaching a large section of humanity.

I would like to place my singular effective strategy to achieve this goal linking my experience in Management and Industrial Engineering.

Management and IE specialists will always hold a special honour and gratitude to Frederick Winslow Taylor for his published work on “The Principles of Scientific Management” (1911) in which he advocated, emphasized, and favoured solving the work problems through improved management methods and raising productivity.

Businesses, modern industries, and even professional sports remain benefited from his methods even today. Taylor’s solution primarily lies in ” Breaking the Job into Elements ” and attempting to reduce the processing time of each.

When this is applied to improve the efficiency and efficacy of the ChatGPT process and results, what stays in front of our eyes is not just the Fields where OpenAI has made its presence felt already but how its growth and spread can be enhanced in the days to come.

Essentially the task lies in ” Breaking each Field into Divisions ” and applying the technique in the same manner as done for the Field.

If the Field is Marketing, then the Divisions would be ” Sales ; Segmentation ; Product LifeCycle ; Marketing Research ; and so on. If the Field is Retail, then the Divisions would be ” Supply Chain ; Inventory Management ; Logistics ; Customer Service ; and so on. If the Field is Constitution, then the Divisions would be ” Local ; Regional ; National ; Border States ; and Global. If the Field is Warfare, then the Divisions would be Army, Navy, Airforce, Infowar, Cyberwar and so on. The dataset used to train AI should relate and conform to the Divisions as specified above for accurate answers/results.

Most of you may have or may not have heard of : 1. ChatGPT, 2. Claude by Anthropic (a Constitutional AI); 3. Character AI (enabling one to speak to historians, legends, experts … to gain their views of how the world is visualised ) ; 4. Adept AI ( Intelligence by enabling humans and computers to work together creatively ); 5. Blenderbot (Meta AI Chatbot); 6. Bard ( Launched by Google to rival ChatGPT. It combines the breadth of the World’s knowledge with the power, Intelligence, and creativity of its large language models); 7. Ellie AI ( enabling e:mail communications ) ; 8. Ernie AI by the Chinese Baidu ; 9. Cohere AI ( A different approach to AI creating Application Programming Interfaces – APIs – avoiding exclusivity ; available to all in cloud platforms ; open access business model with ability to create more enterprise applications ).

What will follow now will be hundreds and thousands of Specific models that will enable easy, more accurate, and less unreliable Chatbots increasing the usage and applications through the Economy. Focus and success of AI, ML, and Data Science researchers on these aspects of Innovation and Creativity will define, direct, and guide the growth of Chatbots in sectors. This is not impossible. This will be a real game-changer. Every professional, educator, and learner will now be kept on his/her toes for months, years, decades, and more.

Tidbit : ” If you are always trying to be normal you will never know how amazing you can be “.

Tuesday, February 7, 2023.

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