---
title: "Can Synthetic Data Replace Real Data?"
url: https://daily.dev/posts/can-synthetic-data-replace-real-data--fyk17dtde
source_url: https://pub.towardsai.net/can-synthetic-data-replace-real-data-aaef5f6b98fd
type: article
source: "Towards AI"
published: 2024-03-11T13:08:16.815Z
updated: 2024-05-09T09:28:05.588Z
tags: ["ai", "machine-learning", "data-science", "privacy", "facial-recognition"]
reading_time: 5
upvotes: 3
comments: 0
language: en
---

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# Can Synthetic Data Replace Real Data?

**[Towards AI](https://daily.dev/sources/tai)** · 5 min read · 3 upvotes · 0 comments

## Summary

Synthetic data can be used to train machine learning models effectively, alleviate biases, account for properties not found in real data, and protect privacy. It is used to generate synthetic face datasets with subject uniqueness, style diversity, and label consistency. The goal is to eventually have fully synthetic datasets without real data.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://pub.towardsai.net/can-synthetic-data-replace-real-data-aaef5f6b98fd>

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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), [#privacy](https://daily.dev/tags/privacy), [#facial-recognition](https://daily.dev/tags/facial-recognition)

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