YouWhat is this?
Zama's bounty program: it pays developers to solve Fully Homomorphic Encryption (FHE) challenges built on Zama's open source libraries, as an experiment to advance the whole FHE field.
Zama's bounty program: it pays developers to solve Fully Homomorphic Encryption (FHE) challenges built on Zama's open source libraries, as an experiment to advance the whole FHE field.Is this a library or a tool, or just a listing of challenges?Neither — it is a listing, not a codebase: the repo holds the rules, a leaderboard and bounty issues, while the actual work happens in Zama's libraries like TFHE-rs, Concrete ML and fhEVM.
Neither — it is a listing, not a codebase: the repo holds the rules, a leaderboard and bounty issues, while the actual work happens in Zama's libraries like TFHE-rs, Concrete ML and fhEVM.How do I actually take part in a bounty?Nothing to install: pick a bounty issue on GitHub and comment on it to compete; for questions there is [email protected], the Zama Discord and the community forum.
Nothing to install: pick a bounty issue on GitHub and comment on it to compete; for questions there is [email protected], the Zama Discord and the community forum.What would I actually be coding with?Zama's own libraries: past seasons rotated between TFHE-rs for FHE in Rust, Concrete ML for privacy-preserving machine learning, and fhEVM for confidential on-chain contracts.
Zama's own libraries: past seasons rotated between TFHE-rs for FHE in Rust, Concrete ML for privacy-preserving machine learning, and fhEVM for confidential on-chain contracts.Is the program still running?It is closed: the page is archived and points readers to a new page for current bounties, so the seasons and leaderboard shown here are historical.
It is closed: the page is archived and points readers to a new page for current bounties, so the seasons and leaderboard shown here are historical.Do I need cryptography experience to compete?Expect a high bar: past bounties meant implementing AES-128 under homomorphic encryption in TFHE-rs or building privacy-preserving ML apps, so strong crypto skills are effectively a prerequisite.
Expect a high bar: past bounties meant implementing AES-128 under homomorphic encryption in TFHE-rs or building privacy-preserving ML apps, so strong crypto skills are effectively a prerequisite.What have past bounties actually asked for?Concrete builds: homomorphic AES-128 and encrypted SQL queries in TFHE-rs, a privacy-preserving Shazam and encrypted DNA ancestry in Concrete ML, plus on-chain apps like a sealed-bid token auction and an encrypted Wordle in fhEVM.
Concrete builds: homomorphic AES-128 and encrypted SQL queries in TFHE-rs, a privacy-preserving Shazam and encrypted DNA ancestry in Concrete ML, plus on-chain apps like a sealed-bid token auction and an encrypted Wordle in fhEVM.Why does Zama pay people to do this?To accelerate the field: Zama wants the community to build FHE applications and drive the technology 'forward by a decade', favoring innovation and new contributions over bug fixes.
To accelerate the field: Zama wants the community to build FHE applications and drive the technology 'forward by a decade', favoring innovation and new contributions over bug fixes.How often did new bounties appear?In seasons: Season 1 launched in Q4 2022 and each season usually ran several weeks to months; the program reached Season 8 before the page was archived.
In seasons: Season 1 launched in Q4 2022 and each season usually ran several weeks to months; the program reached Season 8 before the page was archived.What are similar projects?hashsigs-rs, fhevm, hashsigs-solidity, cpp-sdk, hush, sismo-badges, ethereum-sdk, open-crypto-puzzles
hashsigs-rs, fhevm, hashsigs-solidity, cpp-sdk, hush, sismo-badges, ethereum-sdk, open-crypto-puzzlesWhich topics is it in?ethereum, smart-contracts, community, cryptography, blockchain, encryption, developers, tutorial, rust, research, privacy, machine-learning
ethereum, smart-contracts, community, cryptography, blockchain, encryption, developers, tutorial, rust, research, privacy, machine-learning