Models & Labs
Differentially Private ML with JAX-Privacy Released
Google Research Blogmedium confidence
Why it matters
- →The release of JAX-Privacy could enable developers to build more privacy-conscious AI applications, addressing growing concerns about data security.
Google Research has introduced JAX-Privacy, a framework for implementing differentially private machine learning at scale. This tool aims to enhance privacy in machine learning applications.
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New release of llama.cpp b8991
The latest version b8991 of llama.cpp has been released, featuring updates for various operating systems.
llama.cpp Releases
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llama.cpp update enhances compatibility and performance
The latest update to llama-mmap improves compatibility with various platforms and model sizes. Key enhancements include support for 32-bit wasm and updates to gguf.cpp style.
llama.cpp Releases
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