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Amazon ’s plunge ( in prevue ) a privacy - preserving service that let AWS client deploy “ lookalike ” AI framework school for one - off troupe - company collaborations .
Called Clean Rooms ML — an branch of AWS ’ existingClean Roomsproduct — the service of process removes the pauperism for AWS customers to deal proprietary data with their outside cooperator to build , civilise and deploy AI model .
“ With Clean Rooms ML , you’re able to train a individual lookalike model across your collective data point , ” Swami Sivasubramanian , VP for data and automobile learning service at AWS , said onstage during a tonic this morning at AWS re : Invent . “ you’re able to keep control of your exemplar and delete them when you ’re done . ”
Clean Rooms ML allows customers to take a small sample of customer platter to generate an expand set of standardised records with a pardner — a lookalike AI manikin . For object lesson , an airline business might take signals about loyal customers and work with an on-line reservation service to offer promotions to new , but very similar , substance abuser .
Clean Rooms ML offers controller to melodic phrase modeling output signal found on particular clientele needs , Sivasubramanian read . In the near future tense , he added , AWS plan to add setting specifically for covering in healthcare .
In a related declaration , Amazon unveiled Clean Rooms Differential Privacy , a amply cope service in Clean Rooms . Clean Rooms Differential Privacy obfuscates the upload of any customer ’s data point while yield “ aggregative insights , ” Amazon says — allow client to get combined insight about things like advertising campaigns , investment conclusion and clinical research without take to expose their proprietary data point .
