Privacy Challenges in Extreme Gradient Boosting
-Editor’s note: This article was originally published on Amazon Science Blog by Dr. Dimitar Jetchev, CTO of Inpher and…
How to Build Machine Learning Models with Private Data Sources on AWS
-This article was originally published on AWS blogs by Conor Moran, Sr. Director, Business Development, Inpher.
AWS users occasionally need to perform analysis on data sources containing private or sensitive inputs. Inpher’s XOR Secret Computing Platform, available in AWS Marketplace, enables data scientists to train and run machine learning models while maintaining data privacy and without trading utility. Data analysis and machine learning performed by XOR can improve model performance with mathematically guaranteed data privacy while ensuring the data never leaves the data source.
Inpher Wins Tech4Trust 2021 Startup Accelerator Program
-This article was originally published on AWS blogs by Conor Moran, Sr. Director, Business Development, Inpher.
AWS users occasionally need to perform analysis on data sources containing private or sensitive inputs. Inpher’s XOR Secret Computing Platform, available in AWS Marketplace, enables data scientists to train and run machine learning models while maintaining data privacy and without trading utility. Data analysis and machine learning performed by XOR can improve model performance with mathematically guaranteed data privacy while ensuring the data never leaves the data source.
EU and U.S. Policymakers Emphasize Privacy-Enhancing Technologies as a Shared Priority in 2021
-Only two months into the year, 2021 has already laid a solid foundation of legislative and regulatory support for…
The Privacy Risk Right Under Our Nose in Federated Learning
-Even if you’ve never heard of Federated Learning (FL) before, it is likely that your data is being processed…
Inpher wins the iDASH Secure Genome Analysis Competition
-Advances in biomedical analytics and AI have revolutionized modern healthcare. Predictive systems in this field allow for better medical…
Accelerating Moore4Medical’s Innovation: Ensuring Patient Privacy in Healthcare AI
-We live in an era where the borders between Pharmaceuticals, MedTech, and the Electronic Components and Systems industry (ECS)…
Better ESG Benchmarking with Secret Computing®
-As asset flows continue to pour into environmental, social and governance (ESG) factored investments, the problem of establishing reliable…
Inpher presents an Innovative solution for AML/CFT at the ACPR Banque de France TechSprint
This article was originally published on AWS blogs by Conor Moran, Sr. Director, Business Development, Inpher.
AWS users occasionally need to perform analysis on data sources containing private or sensitive inputs. Inpher’s XOR Secret Computing Platform, available in AWS Marketplace, enables data scientists to train and run machine learning models while maintaining data privacy and without trading utility. Data analysis and machine learning performed by XOR can improve model performance with mathematically guaranteed data privacy while ensuring the data never leaves the data source.
Inpher’s Research on Privacy-Preserving Machine Learning Published in Two Premier Conferences
This article was originally published on AWS blogs by Conor Moran, Sr. Director, Business Development, Inpher.
AWS users occasionally need to perform analysis on data sources containing private or sensitive inputs. Inpher’s XOR Secret Computing Platform, available in AWS Marketplace, enables data scientists to train and run machine learning models while maintaining data privacy and without trading utility. Data analysis and machine learning performed by XOR can improve model performance with mathematically guaranteed data privacy while ensuring the data never leaves the data source.
How DataCo is Reinventing Data Partnerships by Putting Privacy-Enhancing Technologies to Work
[spb_text_block animation=”none” animation_delay=”0″ simplified_controls=”yes” custom_css_percentage=”no” padding_vertical=”0″…
Inpher Announces Strategic Partnership with In-Q-Tel
This article was originally published on AWS blogs by Conor Moran, Sr. Director, Business Development, Inpher.
AWS users occasionally need to perform analysis on data sources containing private or sensitive inputs. Inpher’s XOR Secret Computing Platform, available in AWS Marketplace, enables data scientists to train and run machine learning models while maintaining data privacy and without trading utility. Data analysis and machine learning performed by XOR can improve model performance with mathematically guaranteed data privacy while ensuring the data never leaves the data source.
