Gradient Launches Echo-2 to Break the Cost Barrier Holding Back the Next Wave of AI Progress

New distributed reinforcement learning system cuts post-training costs by up to 80%, expanding access to advanced AI beyond hyperscale data centersSINGAPORE, Feb. 11, 2026 (GLOBE NEWSWIRE) -- Up to 80 ...
The Lancet

Machine learning prediction of 1-year mortality in older patients with heart failure: a nationwide, multicenter, prospective cohort study

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...
FinanceFeeds

Crypto Machine Learning Algorithms Explained for Beginners

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
EurekAlert!

Decomposition-based AI model enhances Indian stock price forecasting amid macroeconomic shocks

Stock markets are essential for households for wealth creation and for firms for raising financial resources for capacity ...
JD Supra

Not A Categorical Ban: Federal Circuit Narrowed Spectrum of Patent Eligible Machine Learning Claims

Recentive Analytics, Inc. v. Fox Corp., No. 23-2437 (Fed. Cir. 2025) – On April 18, 2025, the Federal Circuit upheld the district court’s dismissal of the case on the ground that the patents were ...
EurekAlert!

Enhancing poisoning attack mitigation in federated learning through perturbation-defense complementarity on historical gradients

Federated Learning (FL) allows for privacy-preserving model training by enabling clients to upload model gradients without exposing their personal data. However, the decentralized nature of FL ...
IEEE

Synergetic Learning System Based on Swarm of Non-Gradient Learners

Abstract: Non-gradient descent learning schemes have recently gained attention for their efficient training and simplification of learning control parameter tuning. However, most methods are designed ...
IEEE

GCFL: A Gradient Correction-Based Federated Learning Framework for Privacy-Preserving CPSS

Abstract: Federated learning, as a distributed architecture, shows great promise for applications in cyber-physical-social systems (CPSS). To mitigate the privacy risks inherent in CPSS, the ...