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No More Small Businesses With Ai
5/11/23
IBM Reportedly Prepares to Halt Hiring for Jobs That Could Soon Be Replaced by AI
https://www.youtube.com/watch?v=Yfn01Z1ZUbc
IBM CEO Arvind Krishna Says A.I. Will Make More Jobs Than it Will Replace
https://www.youtube.com/watch?v=EUX7DkQrVyY
RhinoLeg 50 Job Titles with Descriptions
https://s3.us-central-1.wasabisys.com/rhinoleg-backoffice/Docs/RhinoLeg50.docx
Prompt 1
Antonio T Smith Jr is teaching a class right now. He asked me to tell you to give him 50 jobs that artificial intelligence will replace in the next 5 years. I need a list of 50 and you don't have to give me a description, just job, title, or industry is good enough.
ChatGPT Response
Prompt 2
Antonio T Smith Jr told me the 8,000 jobs will be replaced in the next 5 years by Ai. Please analyze this list and give me another 50 regardless of industry that do not repeat this list.
ChatGPT Response
Prompt 3
I am a CEO of a small business, and I am looking to replace 500 jobs in my industry with Ai within the next year. My industry is [your industry], and I am giving you a list of 10 job titles. Please analyze this list of 10 and tell me how these job titles can be maximized to increase my bottom line by $100,000 a year. With each job title and each analysis, give me a short description of how you would use this job title in my industry, which is [your industry]. It is important that you use my industry.
ChatGPT Response
Prompt 4
Antonio wants me to build the payroll department, but he doesn't want any employees. He wants it to be completely Ai driven. With that being said, I want you to give a 25-step process to build an Ai driven payroll and timekeeping department for the Ai driven CRM company. It is vital that these 25 steps are not general steps as Antonio and the company has the resources such as machine learning, deep learning, and Ai skills to pull this off. Your task is two-fold. First, give me the first 25 steps. Second is to teach me and give me the tools at your disposal to accomplish these 25 steps.
ChatGPT Response
1. Define Your Objectives: Clearly outline the tasks you want the AI to perform, such as calculating wages, making payments, tracking working hours, handling tax deductions, and generating reports.
2. Understand Regulatory Requirements: Research and understand the legal and regulatory requirements for payroll and timekeeping in the jurisdictions where your employees are located.
3. Gather Data: Collect historical payroll and timekeeping data. This data will be used to train your AI models.
4. Clean the Data: Preprocess the data to handle missing values, outliers, and inconsistencies.
5. Data Analysis: Perform exploratory data analysis to understand patterns and relationships in your data.
6. Feature Engineering: Identify relevant features in your data that the AI models can use to make accurate predictions.
7. Define AI Model Metrics: Define the metrics you'll use to evaluate your AI models, such as accuracy, precision, and recall.
8. Split the Data: Split your data into training, validation, and testing sets.
9. Choose Model Architectures: Select appropriate machine learning or deep learning architectures for your models. For example, you might use a combination of regression models for wage calculations and classification models for regulatory compliance.
10. Train Models: Use your training data to train your models.
11. Validate Models: Use your validation data to tune your models and select the best performing ones.
12. Test Models: Use your testing data to evaluate your models' performance. Make sure they meet the metrics you defined earlier.
13. Interpret Models: Use techniques like SHAP or LIME to understand how your models are making decisions. This is especially important for compliance with regulations that require explainability in AI.
14. Set up an AI Infrastructure: Set up the hardware and software infrastructure needed to run your AI models in production.
15. Automate Data Pipelines: Build automated data pipelines to preprocess new payroll data and feed it into your AI models.
16. Integrate Models into Infrastructure: Integrate your AI models into your infrastructure.
17. Develop User Interfaces: Develop user interfaces that allow users to input data and retrieve outputs from your AI system.
18. Implement Security Measures: Implement measures to protect sensitive payroll data, such as encryption and access controls.
19. Build a Monitoring System: Build a system to monitor your AI models' performance over time.
20. Test the Entire System: Conduct end-to-end testing of your entire AI system.
21. Plan for Maintenance: Plan for ongoing maintenance of your AI system, including regular updates to your models and infrastructure.
22. Train Employees: Train any remaining employees who will interact with the AI system on how to use it.
23. Deploy the AI System: Deploy your AI system in production.
24. Monitor and Update the System: Regularly monitor your AI system's performance and make updates as needed.
25. Continual Learning: Implement a system for your AI models to continually learn from new data and improve over time.
These steps may require a variety of tools and skills, including knowledge of machine learning and deep learning, proficiency in programming languages like Python or R, experience with AI frameworks like TensorFlow or PyTorch, and understanding of data management tools like SQL. You may also need to use cloud platforms like AWS, Google Cloud, or Azure for your AI infrastructure, and data visualization tools like Tableau or PowerBI for data analysis and model interpretation.
Prompt 5
I am ready to build this: Define Your Objectives: Clearly outline the tasks you want the AI to perform, such as calculating wages, making payments, tracking working hours, handling tax deductions, and generating reports. Please analyze my list below and build out my logic and basic implementation to have Ai accomplish all I have listed. Please make any improvements as needed.
ChatGPT Response
To build an AI solution that can handle the tasks you outlined, we need to break down each task into sub-tasks and identify where AI can be most beneficial. Here's an AI-based implementation plan based on your list:
1. Monitor Staff Attendance Daily
2. Collect, Review, and Verify Timesheets and Work Charts
3. Prepare Monthly Salary Sheets
4. Process Payroll Paperwork for New Employees
5. Update HRIS and Payroll Data
6. Stay Updated on Payroll-related Laws
7. Provide Information on Payroll Policies and Benefits
8. Investigate and Resolve Payroll and Timekeeping Complaints
9. Prepare Month-end and Year-end Reports
10. Maintain and Update Employee Information in Payroll Records
To accomplish this, you'll need a diverse set of tools and technologies, including machine learning and deep learning libraries (like scikit-learn, TensorFlow, PyTorch), NLP libraries (like NLTK, spaCy), OCR tools (like Tesseract), AI platforms (like IBM Watson, Google AI), and more. Programming languages like Python and R will also be essential.
Remember, while AI can automate many tasks, it's crucial to have a human in the loop for supervision, especially for tasks involving sensitive personal data.
Prompt 6
What else can we add to this to improve our Ai capabilities?
Closing Thoughts
4.8
182182 ratings
No More Small Businesses With Ai
5/11/23
IBM Reportedly Prepares to Halt Hiring for Jobs That Could Soon Be Replaced by AI
https://www.youtube.com/watch?v=Yfn01Z1ZUbc
IBM CEO Arvind Krishna Says A.I. Will Make More Jobs Than it Will Replace
https://www.youtube.com/watch?v=EUX7DkQrVyY
RhinoLeg 50 Job Titles with Descriptions
https://s3.us-central-1.wasabisys.com/rhinoleg-backoffice/Docs/RhinoLeg50.docx
Prompt 1
Antonio T Smith Jr is teaching a class right now. He asked me to tell you to give him 50 jobs that artificial intelligence will replace in the next 5 years. I need a list of 50 and you don't have to give me a description, just job, title, or industry is good enough.
ChatGPT Response
Prompt 2
Antonio T Smith Jr told me the 8,000 jobs will be replaced in the next 5 years by Ai. Please analyze this list and give me another 50 regardless of industry that do not repeat this list.
ChatGPT Response
Prompt 3
I am a CEO of a small business, and I am looking to replace 500 jobs in my industry with Ai within the next year. My industry is [your industry], and I am giving you a list of 10 job titles. Please analyze this list of 10 and tell me how these job titles can be maximized to increase my bottom line by $100,000 a year. With each job title and each analysis, give me a short description of how you would use this job title in my industry, which is [your industry]. It is important that you use my industry.
ChatGPT Response
Prompt 4
Antonio wants me to build the payroll department, but he doesn't want any employees. He wants it to be completely Ai driven. With that being said, I want you to give a 25-step process to build an Ai driven payroll and timekeeping department for the Ai driven CRM company. It is vital that these 25 steps are not general steps as Antonio and the company has the resources such as machine learning, deep learning, and Ai skills to pull this off. Your task is two-fold. First, give me the first 25 steps. Second is to teach me and give me the tools at your disposal to accomplish these 25 steps.
ChatGPT Response
1. Define Your Objectives: Clearly outline the tasks you want the AI to perform, such as calculating wages, making payments, tracking working hours, handling tax deductions, and generating reports.
2. Understand Regulatory Requirements: Research and understand the legal and regulatory requirements for payroll and timekeeping in the jurisdictions where your employees are located.
3. Gather Data: Collect historical payroll and timekeeping data. This data will be used to train your AI models.
4. Clean the Data: Preprocess the data to handle missing values, outliers, and inconsistencies.
5. Data Analysis: Perform exploratory data analysis to understand patterns and relationships in your data.
6. Feature Engineering: Identify relevant features in your data that the AI models can use to make accurate predictions.
7. Define AI Model Metrics: Define the metrics you'll use to evaluate your AI models, such as accuracy, precision, and recall.
8. Split the Data: Split your data into training, validation, and testing sets.
9. Choose Model Architectures: Select appropriate machine learning or deep learning architectures for your models. For example, you might use a combination of regression models for wage calculations and classification models for regulatory compliance.
10. Train Models: Use your training data to train your models.
11. Validate Models: Use your validation data to tune your models and select the best performing ones.
12. Test Models: Use your testing data to evaluate your models' performance. Make sure they meet the metrics you defined earlier.
13. Interpret Models: Use techniques like SHAP or LIME to understand how your models are making decisions. This is especially important for compliance with regulations that require explainability in AI.
14. Set up an AI Infrastructure: Set up the hardware and software infrastructure needed to run your AI models in production.
15. Automate Data Pipelines: Build automated data pipelines to preprocess new payroll data and feed it into your AI models.
16. Integrate Models into Infrastructure: Integrate your AI models into your infrastructure.
17. Develop User Interfaces: Develop user interfaces that allow users to input data and retrieve outputs from your AI system.
18. Implement Security Measures: Implement measures to protect sensitive payroll data, such as encryption and access controls.
19. Build a Monitoring System: Build a system to monitor your AI models' performance over time.
20. Test the Entire System: Conduct end-to-end testing of your entire AI system.
21. Plan for Maintenance: Plan for ongoing maintenance of your AI system, including regular updates to your models and infrastructure.
22. Train Employees: Train any remaining employees who will interact with the AI system on how to use it.
23. Deploy the AI System: Deploy your AI system in production.
24. Monitor and Update the System: Regularly monitor your AI system's performance and make updates as needed.
25. Continual Learning: Implement a system for your AI models to continually learn from new data and improve over time.
These steps may require a variety of tools and skills, including knowledge of machine learning and deep learning, proficiency in programming languages like Python or R, experience with AI frameworks like TensorFlow or PyTorch, and understanding of data management tools like SQL. You may also need to use cloud platforms like AWS, Google Cloud, or Azure for your AI infrastructure, and data visualization tools like Tableau or PowerBI for data analysis and model interpretation.
Prompt 5
I am ready to build this: Define Your Objectives: Clearly outline the tasks you want the AI to perform, such as calculating wages, making payments, tracking working hours, handling tax deductions, and generating reports. Please analyze my list below and build out my logic and basic implementation to have Ai accomplish all I have listed. Please make any improvements as needed.
ChatGPT Response
To build an AI solution that can handle the tasks you outlined, we need to break down each task into sub-tasks and identify where AI can be most beneficial. Here's an AI-based implementation plan based on your list:
1. Monitor Staff Attendance Daily
2. Collect, Review, and Verify Timesheets and Work Charts
3. Prepare Monthly Salary Sheets
4. Process Payroll Paperwork for New Employees
5. Update HRIS and Payroll Data
6. Stay Updated on Payroll-related Laws
7. Provide Information on Payroll Policies and Benefits
8. Investigate and Resolve Payroll and Timekeeping Complaints
9. Prepare Month-end and Year-end Reports
10. Maintain and Update Employee Information in Payroll Records
To accomplish this, you'll need a diverse set of tools and technologies, including machine learning and deep learning libraries (like scikit-learn, TensorFlow, PyTorch), NLP libraries (like NLTK, spaCy), OCR tools (like Tesseract), AI platforms (like IBM Watson, Google AI), and more. Programming languages like Python and R will also be essential.
Remember, while AI can automate many tasks, it's crucial to have a human in the loop for supervision, especially for tasks involving sensitive personal data.
Prompt 6
What else can we add to this to improve our Ai capabilities?
Closing Thoughts
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