Towards Encrypted Large Language Models with FHE

1. 1Understand the basics of Fully Homomorphic Encryption (FHE) and its potential to solve LLM privacy challenges
2. 2Explore the implementation of a LLM layer with FHE, including quantization and compilation to FHE
3. 3Apply FHE to existing LLM models, such as the Hugging Face GPT2 model, to evaluate its effectiveness and complexity

AI engineers and researchers on a team can benefit from understanding the implementation of FHE in LLMs to improve user privacy, while data scientists and product managers can appreciate the potential applications and challenges of this technology

💡 Fully Homomorphic Encryption (FHE) can be used to encrypt large language models, enabling secure and private computations on sensitive data

💡 Encrypting LLMs with FHE can protect user privacy! 🤫