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Nov 4, 2024

Differentially Private finetuning for LLMs

I already explained DP ML in another post 1, so this blog post covers the question, how can we design a service that lets customers finetune Large Language Models in a privacy preserving way. With the rise of data privacy laws like GDPR, DSGVO and CCPA, companies face increased scrutiny on data handling practices. The demand for privacy-preserving AI models is growing, especially in highly regulated industries. Despite this demand, many businesses lack the in-house expertise to implement their own model fine-tuning. Read more

All Posts

  • Differentially Private finetuning for LLMs - Nov 4, 2024
  • Privacy-Preserving Canvas Fingerprinting - Oct 4, 2024
  • Backdooring Linux with Linker Envs the right way - Apr 19, 2024
  • Short story about evading Antivirus Detection - Oct 4, 2022
  • Brief introduction to Differentially Private Machine Learning - Sep 14, 2020
  • 3D-GAN - Sep 4, 2020