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Home > Data Science at Home > Private machine learning done right (Ep. 207)


	Podcast:		Data Science at Home
	Episode:		Private machine learning done right (Ep. 207)
	Category:		Technology
	Duration:		00:26:45
	Publish Date:		2022-10-25 08:08:51
	Description:		There are many solutions to private machine learning. I am pretty confident when I say that the one we are speaking in this episode is probably one of the most feasible and reliable. I am with Daniel Huynh, CEO of Mithril Security, a graduate from Ecole Polytechnique with a specialisation in AI and data science. He worked at Microsoft on Privacy Enhancing Technologies under the office of the CTO of Microsoft France. He has written articles on Homomorphic Encryptions with the CKKS explained series (https://blog.openmined.org/ckks-explained-part-1-simple-encoding-and-decoding/). He is now focusing on Confidential Computing at Mithril Security and has written extensive articles on the topic: https://blog.mithrilsecurity.io/. In this show we speak about confidential computing, SGX and private machine learning References Mithril Security: https://www.mithrilsecurity.io/ BindAI GitHub: https://github.com/mithril-security/blindai Use cases for BlindAI: Deploy Transformers models with confidentiality: https://blog.mithrilsecurity.io/transformers-with-confidentiality/ Confidential medical image analysis with COVID-Net and BlindAI: https://blog.mithrilsecurity.io/confidential-covidnet-with-blindai/ Build a privacy-by-design voice assistant with BlindAI: https://blog.mithrilsecurity.io/privacy-voice-ai-with-blindai/ Confidential Computing Explained: https://blog.mithrilsecurity.io/confidential-computing-explained-part-1-introduction/ Confidential Computing Consortium: https://confidentialcomputing.io/ Confidential Computing White Papers: https://confidentialcomputing.io/white-papers-reports/ List of Intel processors with Intel SGX: https://www.intel.com/content/www/us/en/support/articles/000028173/processors.html https://github.com/ayeks/SGX-hardware Azure Confidential Computing VMs with SGX: Azure Docs: https://docs.microsoft.com/en-us/azure/confidential-computing/confidential-computing-enclaves How to deploy BlindAI on Azure: https://docs.mithrilsecurity.io/getting-started/cloud-deployment/azure-dcsv3 Confidential Computing 101: https://www.youtube.com/watch?v=77U12Ss38Zc Rust: https://www.rust-lang.org/ ONNX: https://github.com/onnx/onnx Tract, a Rust inference engine for ONNX models: https://github.com/sonos/tract
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