{"signature": "0xb5435f8ca2273e8f9508c2b459c06e97877814d6b7540641dac650aa80cb3fde0b37ad6344142dec99651944478370d54b0595624b1f7322e5a04df23f2a8a761b", "application": {"round": "0x274554eb289004e15a7679123901b7f070dda0fa", "answers": [{"type": "email", "hidden": true, "question": "Email Address", "questionId": 0, "encryptedAnswer": {"ciphertext": "ugUOFJ2Da1v1mEOituol2uCsvMvxZC6y0+u6CZUflynxp3MetgUiBHMXvIJoTRs2", "encryptedSymmetricKey": "87c591d757431d83bd1a589ff9268b16cf6e84117217e14603e7f09f87e9d4484e03d862cedf96801db00ee9fa250718b5e0bc47ce8217cd322c624b1e5e1a991a82fe48f3ba8deac3143b1302fd86280049713991499c47660e578be886d490cfd0f711177d6b79db2610561e888d45fad090947e3e65d6cacdd28e172915590000000000000020e78e964662dc0eb249dd66a9832a5bd056c28ace52ce0052153dfb99c619ba197ad4251e8f52e85ecd57706b2bdaec91"}}, {"type": "short-answer", "answer": "https://bounties.gitcoin.co/grants/7329/a-decentralized-science-framework-by-crunchdao", "hidden": false, "question": "Previous project funding sources (VC, grants, token sales, etc)", "questionId": 1}, {"type": "number", "answer": "1000", "hidden": false, "question": "Total prior funding for project in USD", "questionId": 2}, {"type": "number", "answer": "4", "hidden": false, "question": "Total team size", "questionId": 3}, {"type": "number", "answer": "6", "hidden": false, "question": "How old is the project? (Months)", "questionId": 4}, {"type": "address", "hidden": true, "question": "If you participated in past grant rounds using a different project payout wallet address, please share it here:", "questionId": 5, "encryptedAnswer": {"ciphertext": "VPXmVYyiGCX/etrznai+QDOXUEVnZYe6binhvjQc4P4=", "encryptedSymmetricKey": "d77e1277f941263f1f7d4c878c6e78e9b76ff80e67a3dbcedbcf02b08fc5a12ee390c7e34df5b70eb4698d20a4694f0d48b60432862d0bc29783bd1c1cb8922c5cb99b05910566333ed6517be97949ec281b4a7178197a9e4c5808905e4590b20b3273d1abe4df2dc5494190286b8da7c092de195156bbff70d4368d6afc0701000000000000002090b3212256035924dee2e66de4cd62e5c8a230812e9aa1d149c75165fa14c39fa2bb7b3664f2f6cfd16a116011034395"}}, {"type": "paragraph", "answer": "Twitter @crunchdao\nDiscord @crunchdao\nTelegram @crunchdao", "hidden": false, "question": "Profiles or socials of other main team members publicly associated with project", "questionId": 6}, {"type": "multiple-choice", "answer": "Yes", "hidden": true, "question": "Have you read and confirmed your grant abides by the Program General Eligibility Policy? https://gitcoin.notion.site/Gitcoin-Grants-Beta-Round-Eligibility-b7fca9fd3c26450b89ded11caaa6497f", "questionId": 7}, {"type": "paragraph", "answer": "We plan the growth in the use of ZK Tech both to move towards homomorphic tournaments and to make private-data-based research reproducible. Part of the finalists of the DeSci London 2023 Hackathon, our Lead Quant, Matteo Manzi, presented [our work](https://desci.crunchdao.com/projects/crunchdao/desci-london) on the use of IPFS to foster the reproducibility of machine learning papers.", "hidden": true, "question": "How does your project fit into the ZK Tech round eligibility criteria? ", "questionId": 8}, {"type": "paragraph", "answer": "We've built this web3 solution integrating Metamask and IPFS: https://desci.crunchdao.com/projects", "hidden": false, "question": "If you've participated in past grant rounds, please share any new updates or milestones from the prior months", "questionId": 9}, {"type": "paragraph", "hidden": false, "question": "Anything else you'd like to share about your project, previous work, or other project affiliations? Anything you'd like to add that has not been covered?", "questionId": 10}, {"type": "multiple-choice", "hidden": true, "question": "Does 50% of your team reflect the diversity of the community your project serves with a particular emphasis on including women, Black, Indigenous, and People of Color (BIPoC), individuals with disabilities, and members of the LGBTQ+ community?", "questionId": 11, "encryptedAnswer": {"ciphertext": "se5HV06UotaeDe6k7G3ZwkycOV5ueWywRyeLt+6331s=", "encryptedSymmetricKey": "812daf7c3023eaee0aaccc255aad0f42faecf1fea4e50f2628438f6c09b8af4ac8520ac7f801515cd516fae399f31712a972504af2e989bdcf368bf8b879a1e59bedd4f25922a57fa7889a31f997263d678b5b5c241d16c9fff79b7bde83c0915cbaf3afa74d57510b28af40cf5521d90f881b34911b11003bfdf157f9fd1cd200000000000000208c715ab4b11ace0f72089d2754b3ba36bfe32ba0ae2af520019bd796efa0d0eee86e5c56c29f329ed8af7818fb407e84"}}], "project": {"id": "1:0x03506eD3f57892C85DB20C36846e9c808aFe9ef4:736", "title": "CrunchDAO", "logoImg": "bafkreiba6v3yy2alegcvjphvd6c3pe3n7tfwl7jhs6crddqdauxl26qj7u", "metaPtr": {"pointer": "bafkreicg6z324wcyhemykpcypkf4ji4m4a7cc34igqvbi23plckctyalpu", "protocol": "1"}, "website": "https://www.crunchdao.com/", "bannerImg": "bafkreiak7ba7kn5vepjkubj5wtxzxwd6tkremqbsiees5cz7xh3esfwjve", "createdAt": 1682084235156, "userGithub": "cuperto", "credentials": {"github": {"type": ["VerifiableCredential"], "proof": {"jws": "eyJhbGciOiJFZERTQSIsImNyaXQiOlsiYjY0Il0sImI2NCI6ZmFsc2V9..9nNe3PtFe-Dv7_k_yZ7M8x6p53VlWId282BJwclLBT2pRspWrXS0KJjrLQb2YWvvUOGC963zpsyc4fUhNOKkDw", "type": "Ed25519Signature2018", "created": "2023-04-21T13:47:15.796Z", "proofPurpose": "assertionMethod", "verificationMethod": "did:key:z6MkghvGHLobLEdj1bgRLhS4LPGJAvbMA1tn2zcRyqmYU5LC#z6MkghvGHLobLEdj1bgRLhS4LPGJAvbMA1tn2zcRyqmYU5LC"}, "issuer": "did:key:z6MkghvGHLobLEdj1bgRLhS4LPGJAvbMA1tn2zcRyqmYU5LC", "@context": ["https://www.w3.org/2018/credentials/v1"], "issuanceDate": "2023-04-21T13:47:15.796Z", "expirationDate": "2023-07-20T13:47:15.796Z", "credentialSubject": {"id": "did:pkh:eip155:1:0x6279e0BDdC76B8aDCa38585fEE25d763DA058b03", "hash": "v0.0.0:yoY+Nq5cCtMo+APizO0VGzD8ZSenZ0w0yabGJOu5eBk=", "@context": [{"hash": "https://schema.org/Text", "provider": "https://schema.org/Text"}], "provider": "ClearTextGithubOrg#crunchdao#48659114"}}}, "description": "# Overview \n\nCrunchDAO is a Decentralised Autonomous Organization of over 2,500 data scientists and 500 PhDs utilizing collective intelligence to solve complex problems, powered by a tokenomics model.\n\nOur DeSci framework is twofold:\n\n- We crowdsource machine learning predictions and models through periodic tournaments;\n- We open our research on all quantitative questions and decisions to the DAO.\n\nCrunchDAO is about periodic competitions with supervised learning problems at their core. Our focus is on leveraging Web3 collective intelligence to identify patterns in data, particularly associated with complex systems, by crowdsourcing. It serves as a secure intermediary, enabling data scientists to keep control of their models while powering institutions.\n\nThe predictions submitted to the competition inform the ensemble output of the Decentralised Autonomous Organization (DAO). Members have access to an [encrypted, quantized datasets](https://docs.crunchdao.com/tournament/data), create their prediction model and submit predictions on the given test set (without sharing their Intellectual Property, i.e., their models).\n\n# ZK Technology in CrunchDAO\n\nWe plan the growth in the use of ZK Tech both to move towards homomorphic tournaments and to make private-data-based research reproducible. Part of the finalists of the DeSci London 2023 Hackathon, our Lead Quant, Matteo Manzi, presented [our work](https://desci.crunchdao.com/projects/crunchdao/desci-london) on the use of IPFS to foster the reproducibility of machine learning papers.\n\n# Synergies with DeSci\n\n[CrunchDeSci](https://cointelegraph.com/news/decentralized-science-is-key-to-fixing-academic-research) is CrunchDAO\u2019s decentralized science platform: a community-led, Open Science research framework that allows users to build knowledge incrementally through the scientific research papers proposed on its platform.\n\nOur DeSci platform, through the use of ZK Tech, will allow users to access and contribute to our library of scientific papers and knowledge. Our technical roadmap lays out our plans for advancement with ZK Tech. We are actively performing R&D on [ZKML](https://github.com/zkml-community/awesome-zkml) throughout our work, and plan to integrate in our pipeline homomorphic encryption and ZKML tools. We are equally collaborating with [Zama](https://www.zama.ai/), also based in Paris, and in future we plan to integrate [concreteML](https://github.com/zama-ai/concrete-ml) into our work. This is relevant, not only for the field of finance, but many other potential applications, including [healthcare](https://www.molecule.to/).\n\nOur progress can be monitored through our [DeSci platform](https://desci.crunchdao.com/projects), our [Twitter](https://twitter.com/CrunchDAO) and our [LinkedIn](https://www.linkedin.com/company/crunchdao-com/).\n\nThis grant will enable us to define positions to develop this framework and to actively use it both inside the DAO and with our research group, working on Dynamical Systems Theory, Machine Learning and Quantitative Finance.", "lastUpdated": 0, "projectGithub": "crunchdao", "projectTwitter": "crunchdao"}, "recipient": "0x6279e0BDdC76B8aDCa38585fEE25d763DA058b03"}}