GPTs are not just for OpenAI and ChatGPT. GPT now refers to a type of AI model mainly used for text-based tasks. Many businesses have created GPT-powered tools to empower employees and streamline tasks. There are GPT apps and tools available for personal use.
This conceptual course discusses the foundations of GPT models and shows you who can use a GPT tool and how.
By Jasmin Ludolf, Data Science Content Developer, DataCamp
Basics of a GPT model and tool. GPT capabilities, who can use them, and when it's appropriate to fit them into your workflow.
- The GPT model was introduced by OpenAI in 2018
- A large language model understands and generates human-like text
- Generative pre-trained transformer
- Generative - creates new content
- Pre-trained - learned from a lot of data, usually public data
- Transformer - underlying model structure is specialized in working with text
- GPT capabilities: generate, summarize, translate
- GPT for personal use
- How do GPT models work?
- Analyze user-inputted text (prompts)
- Against patterns learned from data
- GPT model training - extensive data, typically from public sources, learns general tasks like summarization and results in a pre-trained model
- GPT model fine-tuning on specialized data
- Businesses carefully define this data, keeping security and privacy in mind
- GPTs are for everyone
- How to benefit from a GPT tool
- Identify repetitive or time-consuming tasks in our workflow
- GPT tools enabled for a video conference
- Adopting GPT models
- Benefits and limitations of GPT tools
- Deciding if it's appropriate to use
- Deep dive into safe use and input and outputs
- When to use a GPT tool
- Do we require accurate results? If yes, consider other methods
- Is the result verifiable? If yes, use the tool then check the results
- Does it require private information? If yes, pause to understand vulnerabilities
- Does we need ownership? If yes, seek legal counsel first
Core principles behind responsible AI and use GPT tools safely. GPT inputs and outputs, how to construct effective prompts and evaluate the results.
- Responsible AI - The practice of developing and using AI systems in a way that benefits society while minimizing the risk of negative consequences
- User considerations
- Behavior complies with laws and regulations
- Different depending on location and industry
- Treat everyone equally without discrimination
- Understand how the tool works
- Respect individual rights
- Protect business data
- Applies to prompts and outputs
- Check the policy
- General input considerations
- Personally identifiable information
- Proprietary information
- General output considerations
- Bias: unfairly favors one outcome
- Context tracking: losing track of the conversation
- Hallucination: confident incorrect answer
- Prompt engineering
- Be specific
- Provide example
- Provide template
- Iterate, refine and improve
- Validation techniques
- Evaluate the output ourselves with domain knowledge
- Compare the results or ask an expert
- Use question-and-answering
- Always proofread
Practice with some real-life examples. Quick how-to guide to get you started on writing prompts and using the tools.
- Real-life examples
- Content creation
- Communication
- Text processing
- Research & planning