ChatGPT Cheat Sheet
What sets ChatGPT apart from other chatbots is its power and versatility — chiefly, ChatGPT can adjust its current output based on its previous conversations. Users also found that ChatGPT’s uses go beyond simple back-and-forth conversations. It can generate a variety of different text-based material, and provide easy-to-understand, conversational answers to potentially difficult or complex questions.
The more parameters one has, the more dynamic it is. The first iteration of GPT had 117 million parameters. GPT-2 had 1.5 billion parameters, and GPT-3 had over 175 billion parameters. ChatGPT is based on a slightly updated GPT-3.5, which means it has even more parameters than GPT-3. That’s what makes it so powerful.
Here are ten ways ChatGPT can 10x the developer productivity:
- Text completion
- Sentiment analysis
- Named entity recognition
- Information extraction
- Text summarisation
- Automated Content Generation
- Code generation
- Natural language processing
- Conversational AI
- Text correction and refinement
Text completion
Consider a scenario where a developer is building a text completion system for an email application. The user might start typing an email, and the text completion system would suggest words or phrases to complete the sentence.
Input:
"Dear [Name],
I hope this email finds you"
Sentiment analysis
Consider a scenario where a developer is building a system to analyze customer reviews of a product. The system would use ChatGPT to determine the sentiment expressed in each review, such as whether it is positive, negative, or neutral. This information could then be used to identify trends and patterns in customer feedback, helping the company to improve its products and customer service.
Input: "This product is amazing! I highly recommend it to anyone looking for a high-quality solution."
Output: Positive sentiment (confidence score: 0.95)
Named entity recognition
Consider a scenario where a developer is building a system to extract information from news articles. The system would use ChatGPT to identify named entities in each article, such as the people, organizations, and locations mentioned. This information could then be used to generate summaries, create event timelines, or perform other types of analysis.
Input:
"President Barack Obama visited China last week to meet with President Xi Jinping and discuss economic and security issues."
Output:
Named entities:
Barack Obama (Person)
China (Location)
President Xi Jinping (Person)
In this way, developers can use ChatGPT to build systems that perform named entity recognition, making it easier to extract meaningful information from text and to perform advanced analysis and visualization. These systems can be integrated into a variety of applications, such as news aggregation and content management, to help organizations make data-driven decisions and improve the customer experience.
Information extraction
Consider a scenario where a developer is building a system to extract information from resumes. The system would use ChatGPT to identify key information in each resume, such as the candidate’s name, education, and work experience. This information could then be used to generate candidate profiles, perform candidate matching, or perform other types of analysis.
Input:
"John Doe 123 Main Street Anytown, USA 12345 (123) 456-7890 john.doe@email.com
Objective: To obtain a position as a software engineer in a dynamic and growing company.
Education:
Bachelor of Science in Computer Science, Anytown University, Anytown, USA, May 20XX
Master of Science in Computer Science, Anytown University, Anytown, USA, May 20YY
Work Experience:
Software Engineer, ABC Company, Anytown, USA, 20XX - Present
Junior Software Engineer, DEF Company, Anytown, USA, 20YY - 20XX
Skills:
Strong proficiency in Java, Python, and C++
Experience with software development methodologies such as Agile and Scrum
Knowledge of databases and SQL
Output:
Name: John Doe
Address: 123 Main Street, Anytown, USA, 12345
Phone: (123) 456-7890
Email: john.doe@email.com
Objective: To obtain a position as a software engineer in a dynamic and growing company.
Education:
Bachelor of Science in Computer Science, Anytown University, Anytown, USA, May 20XX
Master of Science in Computer Science, Anytown University, Anytown, USA, May 20YY
Work Experience:
Software Engineer, ABC Company, Anytown, USA, 20XX - Present
Junior Software Engineer, DEF Company, Anytown, USA, 20YY - 20XX
Skills:
Strong proficiency in Java, Python, and C++
Experience with software development methodologies such as Agile and Scrum
Knowledge of databases and SQL
Text summarisation
Consider a scenario where a developer is building a text summarisation system for news articles. The user might provide the system with the full text of a news article, and the text summarisation system would generate a concise summary of the most important information.
Input:
"The United States economy grew by 4.6% in the first quarter of 2022, according to the latest data from the Bureau of Economic Analysis. The growth was driven by a rebound in consumer spending and a surge in business investment. The data also showed that the unemployment rate fell to its lowest level in more than a decade, with job gains in industries such as manufacturing and construction.
The strong economic growth was welcomed by policymakers and economists, who noted that it was a positive sign for the continued recovery of the economy. However, some experts warned that the recovery may not be sustained in the long term, as the growth was largely driven by government stimulus and may not be sustainable without further support."
Automated Content Generation
Consider a scenario where a developer wants to generate product descriptions for a clothing website. The developer would first gather a large dataset of product descriptions for similar clothing items, and then use that data to train ChatGPT.
Input:
"Product: Red T-Shirt
Material: 100% Cotton
Features: Soft, comfortable, breathable"
Code generation
Consider a scenario where a developer is building an application that needs to perform a specific task, such as fetching data from an API and displaying it in a table. The developer could use ChatGPT to generate the code needed to perform the task, rather than writing it manually.
Input: "Generate code to fetch data from an API and display it in a table using Python and the Requests library."
Natural language processing
Consider a scenario where a developer is building a text classification system to categorize customer feedback into different categories, such as positive, negative, or neutral. The developer would first gather a large dataset of customer feedback, and then use that data to train ChatGPT.
Input: "I love this product, it's amazing!"
Conversational AI
Consider a scenario where a developer is building a chatbot for a customer service application. The chatbot would use ChatGPT to understand and generate responses to customer inquiries. When a customer asks a question, the chatbot would use its training data to determine the most relevant response, and then generate a response using ChatGPT.
Input: "What is the return policy for this product?"
Text correction and refinement
Consider a scenario where a developer is building a system that helps users write more effective emails. The system would use ChatGPT to suggest improvements to the user’s text, such as correcting spelling and grammar errors, rephrasing awkward or confusing sentences, and suggesting more effective word choices.
Input: "hi i hope your doin well. i wuld like to set up a meeting for nex week to disscuss the project."
Output: "Hi, I hope you're doing well. I would like to set up a meeting for next week to discuss the project."
Conclusion
ChatGPT can help developers automate many tasks, freeing up time and effort for more strategic and creative tasks. ChatGPT can help developers streamline their work and automate many tasks, freeing up time for more strategic and creative tasks. I hope you liked the content and this can surely help you ease your day-to-day task