公开(公告)号：US11755709B2

公开(公告)日：2023-09-12

申请号：US17676797

申请日：2022-02-21

申请人： SHARECARE AI, INC.

发明人： Axel Sly ,  Srivatsa Akshay Sharma ,  Brett Robert Redinger ,  Devin Daniel Reich ,  Geert Trooskens ,  Meelis Lootus ,  Young Jin Lee ,  Ricardo Lopez Arredondo ,  Frederick Franklin Kautz, IV ,  Satish Srinivasan Bhat ,  Scott Michael Kirk ,  Walter Adolf De Brouwer ,  Kartik Thakore

IPC分类号： G06F21/32 ,  G06F21/45 ,  G06N20/00 ,  H04L9/32 ,  G16H10/60 ,  G06K7/14 ,  G06N5/04 ,  H04L9/08 ,  G06V40/70 ,  G06K19/06 ,  G06F18/214 ,  G06V10/74 ,  G06V10/77 ,  G06V10/80 ,  G06V10/44 ,  G06V40/16 ,  G06V10/774 ,  H04L9/40 ,  G06N3/08 ,  G06N3/04

CPC分类号： G06F21/32 ,  G06F18/214 ,  G06F21/45 ,  G06K7/1417 ,  G06K19/06037 ,  G06N5/04 ,  G06N20/00 ,  G06V10/451 ,  G06V10/761 ,  G06V10/774 ,  G06V10/7715 ,  G06V10/803 ,  G06V40/161 ,  G06V40/168 ,  G06V40/70 ,  G16H10/60 ,  H04L9/085 ,  H04L9/0841 ,  H04L9/0866 ,  H04L9/0894 ,  H04L9/3228 ,  H04L9/3231 ,  H04L9/3236 ,  H04L9/3239 ,  H04L9/3242 ,  H04L9/3247 ,  H04L9/3297 ,  G06N3/04 ,  G06N3/08 ,  H04L63/0861

摘要： The technology disclosed relates to authenticating users using a plurality of non-deterministic registration biometric inputs. During registration, a plurality of non-deterministic biometric inputs are given as input to a trained machine learning model to generate sets of feature vectors. The non-deterministic biometric inputs can include a plurality of face images and a plurality of voice samples of a user. A characteristic identity vector for the user can be determined by averaging feature vectors. During authentication, a plurality of non-deterministic biometric inputs are given as input to a trained machine learning model to generate a set of authentication feature vectors. The sets of feature vectors are projected onto a surface of a hyper-sphere. The system can authenticate the user when a cosine distance between the authentication feature vector and a characteristic identity vector for the user is less than a pre-determined threshold.

公开(公告)号：US11177960B2

公开(公告)日：2021-11-16

申请号：US17235889

申请日：2021-04-20

申请人： Sharecare AI, Inc.

发明人： Axel Sly ,  Srivatsa Akshay Sharma ,  Brett Robert Redinger ,  Devin Daniel Reich ,  Geert Trooskens ,  Meelis Lootus ,  Young Jin Lee ,  Ricardo Lopez Arredondo ,  Frederick Franklin Kautz, IV ,  Satish Srinivasan Bhat ,  Scott Michael Kirk ,  Walter Adolf De Brouwer ,  Kartik Thakore

IPC分类号： H04L9/32 ,  H04L9/08 ,  G06N20/00 ,  G06K7/14 ,  G06N5/04

摘要： The technology disclosed relates to authenticating users using a plurality of non-deterministic registration biometric inputs. During registration, a plurality of non-deterministic biometric inputs are given as input to a trained machine learning model to generate sets of feature vectors. The non-deterministic biometric inputs can include a plurality of face images and a plurality of voice samples of a user. A characteristic identity vector for the user can be determined by averaging feature vectors. During authentication, a plurality of non-deterministic biometric inputs are given as input to a trained machine learning model to generate a set of authentication feature vectors. The sets of feature vectors are projected onto a surface of a hyper-sphere. The system can authenticate the user when a cosine distance between the authentication feature vector and a characteristic identity vector for the user is less than a pre-determined threshold.

公开(公告)号：US11915802B2

公开(公告)日：2024-02-27

申请号：US16985183

申请日：2020-08-04

申请人： SHARECARE AI, INC.

发明人： Brett Robert Redinger ,  Kartik Thakore ,  Sandra Ann R Steyaert ,  Walter Adolf De Brouwer ,  Srivatsa Akshay Sharma ,  Lijing Guo

IPC分类号： G16H10/40 ,  G06F16/27 ,  G16H70/60 ,  G06F9/451 ,  G16B45/00 ,  G16B50/30 ,  G06F16/13 ,  G06F9/50 ,  G06F9/48

CPC分类号： G16H10/40 ,  G06F9/451 ,  G06F9/4881 ,  G06F9/5027 ,  G06F9/5061 ,  G06F16/134 ,  G06F16/27 ,  G16B45/00 ,  G16B50/30 ,  G16H70/60 ,  G06F9/5066 ,  G06F9/5072

摘要： The technology disclosed relates to efficient tertiary analysis of genomic data. The technology disclosed includes splitting a genomic data file into a plurality of segments, and storing segments in the plurality of segments across nodes of a distributed storage system, pushing the segments from the nodes of the distributed storage system to nodes of a distributed, in-memory computing engine, distributing directives of tertiary analysis job contexts for the genomic data file across the nodes of the distributed, in-memory computing engine, directly executing the distributed directives on the segments stored on the nodes of the distributed, in-memory computing engine to cause parallel processing of the segments, and aggregating results of the parallel processing across the nodes of the distributed, in-memory computing engine to produce an output.

公开(公告)号：US11811794B2

公开(公告)日：2023-11-07

申请号：US17319025

申请日：2021-05-12

申请人： Sharecare AI, Inc.

发明人： Gabriel Gabra Zaccak ,  William Hartman ,  Andrés Rodriguez Esmeral ,  Devin Daniel Reich ,  Marina Titova ,  Brett Robert Redinger ,  Philip Joseph Dow ,  Satish Srinivasan Bhat ,  Walter Adolf De Brouwer ,  Scott Michael Kirk

IPC分类号： H04L9/40 ,  G06N20/20

CPC分类号： H04L63/1416 ,  G06N20/20

摘要： The technology disclosed provides systems and methods related to preventing exfiltration of training data by feature reconstruction attacks on model instances trained on the training data during a training job. The system comprises a privacy interface that presents a plurality of modulators for a plurality of training parameters. The modulators are configured to respond to selection commands via the privacy interface to trigger procedural calls. The procedural calls modify corresponding training parameters in the plurality of training parameters for respective training cycles in the training job. The system comprises a trainer configured to execute the training cycles in dependence on the modified training parameters. The trainer can determine a performance accuracy of the model instances for each of the executed training cycles. The system comprises a differential privacy estimator configured to estimate a privacy guarantee for each of the executed training cycles in dependence on the modified training parameters.

公开(公告)号：US11321447B2

公开(公告)日：2022-05-03

申请号：US17235876

申请日：2021-04-20

申请人： SHARECARE AI, INC.

发明人： Axel Sly ,  Srivatsa Akshay Sharma ,  Brett Robert Redinger ,  Devin Daniel Reich ,  Geert Trooskens ,  Meelis Lootus ,  Young Jin Lee ,  Ricardo Lopez Arredondo ,  Frederick Franklin Kautz, IV ,  Satish Srinivasan Bhat ,  Scott Michael Kirk ,  Walter Adolf De Brouwer ,  Kartik Thakore

IPC分类号： G06K9/00 ,  G06F21/45 ,  G06N20/00 ,  H04L9/32 ,  G16H10/60 ,  G06F21/32 ,  G06K9/62 ,  G06K7/14 ,  G06N5/04 ,  H04L9/08 ,  H04L29/06 ,  G06N3/08 ,  G06N3/04

摘要： The technology disclosed relates to authenticating users using a plurality of non-deterministic registration biometric inputs. During registration, a plurality of non-deterministic biometric inputs are given as input to a trained machine learning model to generate sets of feature vectors. The non-deterministic biometric inputs can include a plurality of face images and a plurality of voice samples of a user. A characteristic identity vector for the user can be determined by averaging feature vectors. During authentication, a plurality of non-deterministic biometric inputs are given as input to a trained machine learning model to generate a set of authentication feature vectors. The sets of feature vectors are projected onto a surface of a hyper-sphere. The system can authenticate the user when a cosine distance between the authentication feature vector and a characteristic identity vector for the user is less than a pre-determined threshold.