Concrete ML v1.9: TFHE-rs Compatibility and Faster LLM Fine-tuning

Concrete ML v1.9 introduces several advancements, including support for the TFHE-rs ciphertext format, enhancing integration with Rust-based fully homomorphic encryption (FHE) pipelines. This update also optimizes the LoRA LLM fine-tuning protocol and offers new example notebooks, such as a fine-tuned LLAMA model for math problem-solving under FHE on GPUs. Additionally, Zama launches Concrete ML Extensions, a client SDK for building FHE-enabled mobile applications, highlighting the potential of secure, private data processing on devices. The SDK, which can be compiled to Swift for iOS, allows encryption and key management natively, promising further developments with upcoming iOS demo applications.

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