L2
blindai
L2 | blindai | |
---|---|---|
2 | 6 | |
184 | 491 | |
- | 0.4% | |
0.0 | 8.0 | |
over 1 year ago | about 2 months ago | |
Rust | Rust | |
MIT License | Apache License 2.0 |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
L2
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Announcing Burn: New Deep Learning framework with CPU & GPU support using the newly stabilized GAT feature
this is really cool!!! btw i also made a very small toy library years ago in rust too !https://github.com/bilal2vec/L2
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Corgi: Rust neural network/dynamic automatic differentiation library I have been working on
this is really cool! i wrote a library a lot like this last year (https://github.com/bilal2vec/L2) and wrote up a very WIP blog post (https://bilal2vec.github.io/blog/rust/2020/08/02/writing-a-machine-learning-library-in-rust.html) about how i made it if y'all are interested ;)
blindai
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[D] Any options for using GPT models using proprietary data ?
We are working on an open-source project, BlindAI (https://github.com/mithril-security/blindai) to answer exactly that: privacy when sending data to remote AI models.
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[P] Secret Whisper: Deploy OpenAI Whisper model with privacy using BlindAI
BlindAI (https://github.com/mithril-security/blindai) is an open-source confidential AI deployment. By using secure enclaves (Intel SGX for now, soon AMD SEV and Nvidia Confidential Computing), we provide end-to-end protection for users’ data, even when sending it to the Cloud for AI inference. You can see the gains of BlindAI on the scheme below:
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[P] Introducing BlindAI, an Open-source, fast and privacy-friendly AI deployment solution. Benefit from state-of-the-art AI without ever revealing your data!
Good thing with enclave is that the hardware protection enable us to use regular AES to secure communication with the enclave, which means no ciphertext expansion and lightweight client side. We do not need to have a complicated client side, we just need a slightly modified TLS client with additional security checks, like remote attestation but you can have a look on our client side it's light (https://github.com/mithril-security/blindai/tree/master/client).
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BlindAI: fast and privacy-friendly AI deployment solution in Rust
I am glad to introduce BlindAI, an AI deployment solution, leveraging secure enclaves, to make remotely hosted AI models privacy friendly. We leverage the tract project as our inference engine to serve AI models in ONNX format inside an enclave. We also use the Rust SGX SDK to use Rust for our secure enclave for AI.
- BlindAI: Open-source, fast and privacy-friendly AI deployment solution in Rust
What are some alternatives?
Owlyshield - Owlyshield is an EDR framework designed to safeguard vulnerable applications from potential exploitation (C&C, exfiltration and impact).
incubator-teaclave-sgx-sdk - Apache Teaclave (incubating) SGX SDK helps developers to write Intel SGX applications in the Rust programming language, and also known as Rust SGX SDK.
burn - Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals. [Moved to: https://github.com/Tracel-AI/burn]
onnxruntime-rs - Rust wrapper for Microsoft's ONNX Runtime (version 1.8)
Java-Machine-Learning - Deep learning library for Java, with fully connected, convolutional, and recurrent layers. Also features many gradient descent optimization algorithms.
ire - I2P router implementation in Rust
rsrl - A fast, safe and easy to use reinforcement learning framework in Rust.
steelix - Your one stop CLI for ONNX model analysis.
whatlang-rs - Natural language detection library for Rust. Try demo online: https://whatlang.org/
incubator-teaclave-trustzone-sdk - Teaclave TrustZone SDK enables safe, functional, and ergonomic development of trustlets.
blind_chat - A fully in-browser privacy solution to make Conversational AI privacy-friendly
tract - Tiny, no-nonsense, self-contained, Tensorflow and ONNX inference