How I Gained Singapore’s GPT-4 Immediate Engineering Competitors | by Sheila Teo | Dec, 2023
A deep dive into the methods I discovered for harnessing the facility of Giant Language Fashions
Final month, I had the unbelievable honor of profitable Singapore’s first ever GPT-4 Immediate Engineering competitors, which introduced collectively over 400 prompt-ly sensible members, organised by the Authorities Expertise Company of Singapore (GovTech).
Immediate engineering is a self-discipline that blends each artwork and science — it’s as a lot technical understanding as it’s of creativity and strategic considering. It is a compilation of the immediate engineering methods I discovered alongside the best way, that push any LLM to do precisely what you want and extra!
This text covers the next, with 🟢 referring to beginner-friendly prompting methods whereas 🟠 refers to superior methods:
1. [🟢] Structuring prompts using the CO-STAR framework
2. [🟢] Sectioning prompts using delimiters
3. [🟠] Creating system prompts with LLM guardrails
4. [🟠] Analyzing datasets using only LLMs, without plugins or code —
With a hands-on instance of analyzing a real-world Kaggle dataset utilizing GPT-4
Efficient immediate structuring is essential for eliciting optimum responses from an LLM. The CO-STAR framework, a brainchild of GovTech Singapore’s Information Science & AI group, is a useful template for structuring prompts. It considers all the important thing elements that affect the effectiveness and relevance of an LLM’s response, resulting in extra optimum responses.
Right here’s the way it works:
(C) Context: Present background data on the duty
This helps the LLM perceive the precise situation being mentioned, guaranteeing its response is related.
