AI algorithm enables tracking of brainstem's vital white matter pathways

The signals that drive many of the brain and body's most essential functions—consciousness, sleep, breathing, heart rate and motion—course through bundles of "white matter" fibers in the brainstem, ...

TTT-Discover optimizes GPU kernels 2x faster than human experts — by training during inference

A new technique from Stanford, Nvidia, and Together AI lets models learn during inference rather than relying on static ...

Fundamental emerges from stealth with first major foundation model trained for tabular data

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a ...
Amazon Press Center

Fundamental Announces $255M in Funding and Publicly Launches its Most Powerful Large Tabular Model (LTM)

Through its proprietary LTM, ‘NEXUS’, Fundamental reveals the hidden language of tables to unlock trillions of dollars in enterprise value, while a strategic partnership with AWS accelerates adoption ...
Psychology Today

Navigating the Impacts of AI-Driven Social Media Algorithms

Social media algorithms driven by AI shape far more than what appears on our screens, including how we think, feel, and ...
AlphaGalileo

MLEDGE project proves federated learning can support real-world AI services

After two and a half years of work, the MLEDGE project (Cloud and Edge Machine Learning), led by Professor Nikolaos Laoutaris at IMDEA Networks, ...
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 ...
Frontiers

Technical and legal aspects of federated learning in bioinformatics: applications, challenges and opportunities

Federated learning leverages data across institutions to improve clinical discovery while complying with data-sharing restrictions and protecting patient privacy. This paper provides a gentle ...
IEEE

FedSCOPE: A Comprehensive Evaluation Framework for Federated Learning in Human-Centered Social Computing

Abstract: Federated learning (FL) offers innovative solutions for training complex neural networks on large-scale data without directly accessing participants’ raw data. Owing to its inherent ...