Oasis Cooperates With Meta To Build An Information Protection Platform
Oasis Labs partnered with Meta to build a Secure Multi-Party Computing (SMPC) platform to protect user information.
On July 28, Oasis announced a partnership with Meta and launched a platform for evaluating product fairness and protecting privacy for Instagram users.
Under the partnership agreement, Oasis Labs will build a platform that uses Secure Multi-Party Computing (SMPC) to protect Instagram user information. This first platform will play a key role in determining if an AI model is fair and appropriately mitigating.
Meta is opening a survey for those who are using Instagram. The data will be collected and aggregated by a third-party survey service provider, and Meta will not be able to know the results of the user poll.
The cryptographic techniques being used on the platform, at the scale at which they will be used, are unprecedented. This is the beginning of a new journey. Esteban Arcuate, Director of AI at Meta said:
“We are constantly doing work to show the added benefits AI will carry to persons and society, which calls for deep collaboration each internally and externally. Secure Multi-Stakeholder Computing is a privacy-centric technique designed in partnership with Oasis Labs that allows equity-primarily based effectiveness measurement when preserving the privacy of anyone on the front line.“
Decentralized and Web3 can reach individuals worldwide. When combined with data privacy, this opens up the possibility for companies to reach global audiences, use sensitive data to protect privacy, and build great products rather than treating everyone equally.
Oasis has announced AI development cooperation with Meta since November 2021, but the announcement did not bring about a positive response.
DISCLAIMER: The Information on this website is provided as general market commentary and does not constitute investment advice. We encourage you to do your own research before investing.
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Oasis Cooperates With Meta To Build An Information Protection Platform
Oasis Labs partnered with Meta to build a Secure Multi-Party Computing (SMPC) platform to protect user information.
On July 28, Oasis announced a partnership with Meta and launched a platform for evaluating product fairness and protecting privacy for Instagram users.
Under the partnership agreement, Oasis Labs will build a platform that uses Secure Multi-Party Computing (SMPC) to protect Instagram user information. This first platform will play a key role in determining if an AI model is fair and appropriately mitigating.
Meta is opening a survey for those who are using Instagram. The data will be collected and aggregated by a third-party survey service provider, and Meta will not be able to know the results of the user poll.
The cryptographic techniques being used on the platform, at the scale at which they will be used, are unprecedented. This is the beginning of a new journey. Esteban Arcuate, Director of AI at Meta said:
“We are constantly doing work to show the added benefits AI will carry to persons and society, which calls for deep collaboration each internally and externally. Secure Multi-Stakeholder Computing is a privacy-centric technique designed in partnership with Oasis Labs that allows equity-primarily based effectiveness measurement when preserving the privacy of anyone on the front line.“
Decentralized and Web3 can reach individuals worldwide. When combined with data privacy, this opens up the possibility for companies to reach global audiences, use sensitive data to protect privacy, and build great products rather than treating everyone equally.
Oasis has announced AI development cooperation with Meta since November 2021, but the announcement did not bring about a positive response.
DISCLAIMER: The Information on this website is provided as general market commentary and does not constitute investment advice. We encourage you to do your own research before investing.
Join CoinCu Telegram to keep track of news: https://t.me/coincunews
Follow CoinCu Youtube Channel | Follow CoinCu Facebook page
Harold
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