---
title: "Choosing the right technique: Prompt engineering vs fine-tuning"
url: https://daily.dev/posts/choosing-the-right-technique-prompt-engineering-vs-fine-tuning-5ylcf8vne
source_url: https://www.datasciencecentral.com/choosing-the-right-technique-prompt-engineering-vs-fine-tuning/
type: article
source: "Data Science Central"
published: 2024-01-30T13:55:41.744Z
updated: 2024-05-09T09:21:59.549Z
tags: ["ai", "machine-learning", "data-science", "deep-learning", "genai", "llm", "chatgpt", "prompt-engineering", "bard"]
reading_time: 4
upvotes: 3
comments: 0
language: en
---

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# Choosing the right technique: Prompt engineering vs fine-tuning

**[Data Science Central](https://daily.dev/sources/ds_central)** · 4 min read · 3 upvotes · 0 comments

## Summary

AI models rely on prompt engineering and fine-tuning techniques to improve performance and generate contextually relevant results. Prompt engineering involves crafting optimal prompts to influence AI model outputs, while fine-tuning customizes pre-trained models to specific tasks. Both techniques play different roles in enhancing AI model performance.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.datasciencecentral.com/choosing-the-right-technique-prompt-engineering-vs-fine-tuning/>

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---

Tags: [#ai](https://daily.dev/tags/ai), [#machine-learning](https://daily.dev/tags/machine-learning), [#data-science](https://daily.dev/tags/data-science), [#deep-learning](https://daily.dev/tags/deep-learning), [#genai](https://daily.dev/tags/genai), [#llm](https://daily.dev/tags/llm), [#chatgpt](https://daily.dev/tags/chatgpt), [#prompt-engineering](https://daily.dev/tags/prompt-engineering), [#bard](https://daily.dev/tags/bard)

[View this post on daily.dev](https://daily.dev/posts/choosing-the-right-technique-prompt-engineering-vs-fine-tuning-5ylcf8vne)