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360 Privacy for Machine Learning

Fully Homomorphic Encryption (FHE) can be used to protect both the ML model and the user’s privacy.

Dec 21, 2022
 - 
The Zama Team
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General

Fully Homomorphic Encryption and Post-Quantum Cryptography

Answering the question: is fully Homomorphic encryption quantum resistant?

Oct 5, 2022
 - 
Nigel Smart
, 
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How we monetize our open-source products at Zama

It’s time we built big businesses that actually make the internet safer! Zama's open source strategy aims to do just that.

Aug 2, 2022
 - 
Rand Hindi
, 
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Private Smart Contracts using Homomorphic Encryption

Rand Hindi's talk during ETHcc 2022 about "Private Smart Contracts using Homomorphic Encryption".

Jul 20, 2022
 - 
Rand Hindi
, 
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The FHE.org conference 2022 (Zama-ers presentations)

Showcasing Zama-ers presentations during the FHE.org conference 2022.

Jun 15, 2022
 - 
Jérémy Zaccherini
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The (r)Evolution of FHE

Machine Learning and Homomorphic Encryption.

Mar 10, 2022
 - 
Jeremy Bradley
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Privacy is not secrecy. Privacy is not secrecy. Privacy is not secrecy.
Privacy is not secrecy. Privacy is not secrecy. Privacy is not secrecy.
Privacy is not secrecy. Privacy is not secrecy. Privacy is not secrecy.
Privacy is not secrecy. Privacy is not secrecy. Privacy is not secrecy.
A private matter is something one doesn't want the whole world to know,
A private matter is something one doesn't want the whole world to know,
but a secret matter is something one doesn't want anybody to know.
but a secret matter is something one doesn't want anybody to know.
Privacy is necessary for an open society in the electronic age.
Privacy is necessary for an open society in the electronic age.
Privacy is not secrecy. Privacy is not secrecy. Privacy is not secrecy.
Privacy is not secrecy. Privacy is not secrecy. Privacy is not secrecy.