Data Scientist Ke Zhang’s Research Explores Homomorphic Encryption for Privacy-Preserving Marketing

A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...
The Robot Report

We know how to build smarter robots. Now, we need to learn smarter ways to test them

Atharv Kolhar, a staff test automation engineer at Figure AI, says the robotics industry needs a testing philosophy that ...
JD Supra

AI and Drug Repurposing: Old Drugs, New Tricks, and the IP Questions

The premise is straightforward — we are awash in biological data. The rapid growth of multiomics datasets (genomics, transcriptomics, proteomics, metabolomics, and radiomics) together with ...
TechCircle

Closing healthcare gaps through digital innovation

Digital technologies are increasingly driving healthcare initiatives to bridge the gap between the haves and have-nots ...

Confidential Computing In The AI Era

Confidential computing (CC) emerges as an important solution, utilizing hardware-rooted Trusted Execution Environments to ...
University of Geneva

Precision medicine’s inevitable trajectory toward rare-disease-sized cohorts: implications for machine learning and deep learning

As patients are divided into ever more narrowly defined subgroups, the number of individuals available for research shrinks dramatically. While this approach improves personalization, it also creates ...
Bar and BenchOpinion

National Judicial Reforms Commission: A proposal we ignore at our peril [Part I]

Speaking at the first Supreme Court Bar Association National Conference in Bengaluru, Justice BV Nagarathna of the Supreme ...
Oneindia

Abhinav Piratla: AI Security Architect Revolutionizes Medical Device Protection & Healthcare Safety

Abhinav Piratla, an AI security architect, is closing the critical gap in medical device protection. Discover how his ...
How-To Geek on MSN

Changing these 3 settings instantly makes your Android phone more private

You can change them in less than 2 minutes!
IEEE

Federated Learning: A Survey on Enabling Technologies, Protocols, and Applications

Abstract: This paper provides a comprehensive study of Federated Learning (FL) with an emphasis on enabling software and hardware platforms, protocols, real-life applications and use-cases. FL can be ...
IEEE

An Efficient Framework for Clustered Federated Learning

Abstract: We address the problem of federated learning (FL) where users are distributed and partitioned into clusters. This setup captures settings where different groups of users have their own ...