EurekAlert!

A new AI-based attack framework advances multi-agent reinforcement learning by amplifying vulnerability and bypassing defenses

Researchers have developed a novel framework, termed PDJA (Perception–Decision Joint Attack), that leverages artificial ...
VentureBeat

DeepMind releases Acme, a distributed framework for reinforcement learning algorithm development

VentureBeat presents: AI Unleashed - An exclusive executive event for enterprise data leaders. Network and learn with industry peers. Learn More DeepMind this week released Acme, a framework intended ...
Nature

Distributed Deep Learning and Model Parallelism

Distributed deep learning has emerged as an essential approach for training large-scale deep neural networks by utilising multiple computational nodes. This methodology partitions the workload either ...
EurekAlert!

A graph reinforcement learning framework for real-time distributed multi-robot task allocation

Effective task allocation has become a critical challenge for multi-robot systems operating in dynamic environments like search and rescue. Traditional methods, often based on static data and ...
InfoQ

PrefixRL: Nvidia's Deep-Reinforcement-Learning Approach to Design Better Circuits

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
ascopubs.org

Systematic Review of Privacy-Preserving Distributed Machine Learning From Federated Databases in Health Care

Big data for health care is one of the potential solutions to deal with the numerous challenges of health care, such as rising cost, aging population, precision medicine, universal health coverage, ...
InfoWorld

What is deep reinforcement learning: The next step in AI and deep learning

Reinforcement learning is well-suited for autonomous decision-making where supervised learning or unsupervised learning techniques alone can’t do the job Reinforcement learning has traditionally ...
ZDNet

Google's distributed computing for dummies trains ResNet-50 in under half an hour

Is it better to be as accurate as possible in machine learning, however long it takes, or pretty darned accurate in a really short amount of time? For DeepMind researchers Peter Buchlovsky and ...