With thanks to Eric Vyacheslav on Linkedin, this is Open AI’s recommended strategy for getting the best out of prompting GPT.
1 – write clear instructions
- be specific: Clarity in instructions leads to more relevant outcomes.
- define the desired output length and complexity.
- demonstrate preferred formats.
- minimise ambiguity to enhance model accuracy
2 – provide reference text
- counteract potential fabrications with concrete reference materials.
- reference texts guide the model towards accurate and reliable answers
3 – split complex tasks into simpler subtasks:
- break down tasks to reduce errors and improve manageability.
- consider tasks as workflows of simpler, interconnected steps.
4 – give the model time to ‘think’
- allow the model to process and reason, similar to a human solving a complex problem.
- encourage a “chain of thought” approach for more accurate reasoning
5 – use external tools
- supplement the model’s capabilities with specialized tools for specific tasks.
- leverage resources like text retrieval systems or code execution engines
6 – test changes systematically
- measure improvements with a comprehensive testing approach.
- ensure that modifications lead to overall performance enhancements
Click here for the full guide.
Mondatum Labs is here and ready to support all your machine learning- / GPT- / generative AI art-based project, process, pipeline and workflow requirements.
Contact us for advice, guidance or consultancy – Colin Birch (colin@mondatum.com), John Rowe (john@mondatum.com).
Main image ℅ Search Engine Journal