Machine learning news — deep learning, reinforcement learning, neural architecture search, diffusion models, and new ML frameworks and libraries.
NVIDIA researchers published a study in IEEE Transactions of Medical Imaging investigating whether gradient inversion attacks compromise federated learning safety, finding that such attacks can reconstruct training data …
An artificial intelligence system has solved an 80-year-old mathematics problem, stunning researchers. The AI, developed by a team at a leading research institution, cracked the longstanding challenge in number theory, d…
Researchers at NVIDIA and Harvard Medical School used federated learning to predict clinical outcomes in COVID-19 patients, enabling collaborative model training across institutions without sharing sensitive data. The st…
NVIDIA researchers published a study in Nature Digital Medicine on September 14, 2020, exploring the use of federated learning to advance digital health while preserving patient data privacy. The approach enables collabo…
NVIDIA researchers developed an agentic system for deploying machine learning models to ephemeral SageMaker endpoints, generating runtime code at deployment time from prose artifacts rather than reusable scripts. The app…
Researchers Kumar and Varshney proposed a six-pillar framework to mitigate homogenizing bias in AI models for facial aesthetic evaluation, as detailed in a JMIR preprint. The framework addresses underrepresentation of el…
Researchers at the University of California, San Francisco developed an adaptive deep brain stimulation system that senses step-related neural signals and adjusts stimulation within sub-second timescales, improving gait …
Legioni, a team of AI coding agents that coordinates work and learns from every task, has been released as an open-source tool. The agents plan, implement, review, and test code, with lessons from each session being prom…
AI hiring systems that autonomously reject candidates are indefensible because they learn from a flawed label—'good hire'—which is measured late, confounded, and survivorship-biased, causing models to imitate past gateke…
O'Reilly Media listed a new book, 'ML and Generative AI in the Data Lakehouse,' for June 2026, covering Databricks platform, MLflow, Unity Catalog, and responsible AI. The 448-page title targets intermediate-to-advanced …
Scientists using deep learning algorithms have discovered hundreds of previously unknown small earthquakes deep beneath Antarctica's David Glacier, occurring at depths over 43 miles in an area not associated with plate b…
A developer explains that a neural network is not magic but a mechanical process of weighted detectors stacked in layers, turning raw input into higher-level features to make a decision. The network starts with random we…
A developer added Markdown file support to the Sift RAG stack, touching validation, extraction, MIME types, and a database schema migration. The change required updates across six layers including API validation, content…
JAX's default_device context manager places arrays on the specified device but does not commit them, allowing JAX to move them to other devices. This caused array lookups to take over a second by triggering GPU usage, bu…
Apple released JACCL, an open-source collective communication library for distributed AI training over Thunderbolt 5, at WWDC 2026. The library enables clustering 2–4 Macs with 50–60 Gbps bandwidth and single-digit micro…
A comprehensive guide published in 2026 details 25 retrieval-augmented generation (RAG) strategies, organized into five pipeline layers, to help engineers and researchers move beyond naive RAG implementations that fail i…
Researchers at Hiroshima University and Nagoya University developed a machine learning tool called SPERRFY that decoded how gene activity patterns guide neural wiring across the mouse brain. The study, published in PNAS,…
A developer demonstrates how to use the Python library Astroquery to programmatically access astronomical data from multiple archives, solving the heterogeneity problem of different APIs. The tutorial shows how to resolv…
Researchers developed an XGBoost model that predicts clear-air turbulence by incorporating aircraft-specific characteristics, using pilot reports (PIREPs) and ERA5 reanalysis data. The model outperforms traditional turbu…
A developer built reliably-metrics, an open-source Python library that adds confidence intervals and statistical significance tests to common ML evaluation metrics like AUROC, ECE, and Brier score. The library automatica…