Healthcare IT News

An AI primer: machine learning, federated learning and more

OpenAI's ChatGPT system has sent the topic of artificial intelligence through the roof. But so many professionals across industries, including healthcare, do not truly understand how AI works – ...
InfoQ

Federated Machine Learning and Edge Systems

Federated machine learning is useful for edge devices with limited network bandwidth, since only model updates need to be sent to a central location, instead of large volumes of data Federated machine ...
Forbes

Are Embedded And Federated Machine Learning The Future Of The AI Industry?

Somdip is the Chief Scientist of Nosh Technologies, an MIT Innovator Under 35 and a Professor of Practice (AI/ML) at the Woxsen University. As a leader in the artificial intelligence (AI) domain and a ...
Business Wire

kMoL, a Machine Learning Library for AI Drug Discovery With Federated Learning Capabilities

TOKYO--(BUSINESS WIRE)--Elix, Inc., an AI drug discovery company with the mission of “Rethinking Drug Discovery” (CEO: Shinya Yuki/Headquarters: Tokyo, Japan; hereinafter referred to as “Elix”) has ...
Tech Xplore on MSN

New federated learning algorithm enables private, robust, and fast AI development

Three heads are better than one. Versions of this proverb are found worldwide and throughout history. Yet in the race to ...
Scientific Computing World

How do you leverage federated learning models in drug discovery?

There are a few questions that drug discovery teams need to address before considering the adoption of federated learning techniques. Artificial Intelligence (AI) has become criti ...
Medical Xpress

Federated machine learning enables the largest brain tumor study to-date, without sharing patient data

Researchers at Penn Medicine and Intel Corporation led the largest-to-date global machine learning effort to securely aggregate knowledge from brain scans of 6,314 glioblastoma (GBM) patients at 71 ...
VentureBeat

What is federated learning?

One of the key challenges of machine learning is the need for large amounts of data. Gathering training datasets for machine learning models poses privacy, security, and processing risks that ...
Forbes

IBM Federated Learning Research - Extracting Machine Learning Models From Multiple Data Pools

As machine learning becomes more pervasive in the data center and the cloud there will be a need to share and aggregate information and knowledge but without exposing or moving the underlying data.
BizTech

Federated Machine Learning Gives Enterprises a Competitive AI Advantage

Historically, machine learning models have been trained by consolidating data from multiple sources into a centralized cloud server or data center and then training the model based on the combined ...
Diginomica

Federated machine learning is coming - here's the questions we should be asking

With the introduction of Google's Tensor Flow federated, the hype around federated machine learning is surging. But there are important questions about data privacy, performance and cost that need ...