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Brazil's national soccer teams use sensor-packed smart vests to track player metrics during World Cup matches, with sports-science chief Guilherme Passos once nearly benching a player based on low distance data until vid…
At WWDC 2026, Apple software chief Craig Federighi criticized competitors for "racing forward" with AI without clear regard for users, announcing a ground-up rebuild of the company's digital assistant powered by next-gen…
Ernest Chan presented Conditional Portfolio Optimization (CPO), a machine-learning method that trains a neural network to predict portfolio performance based on market features and then solves a constrained optimization …
Researchers have developed a machine-learning method that detects genetic epilepsy signals in seizure-free baseline EEG recordings, according to a study published in the Journal of Neural Engineering. The 'bag-of-waves' …
An arXiv preprint (arXiv:2606.03995) reports an explainable machine learning model that achieved near-perfect three-class classification of Alzheimer's disease, mild cognitive impairment, and normal cognition using eight…
Researchers from the University of Utah, University of Illinois Chicago, Harvard Medical School, and the University of Pittsburgh have developed a smartwatch-inspired wearable that measures continuous blood pressure usin…
Researchers Thomas Izgin, Andreas Meister, and Isaac Azure developed a machine learning workflow to improve hyperparameter estimation in compartmental pandemic models, achieving 5-day COVID-19 predictions within a 10% er…
Google Chrome is deploying on-device machine learning warnings on Android to flag deceptive or spammy notifications, displaying the sending site, a warning message, and options to unsubscribe or allow future alerts. The …
Researchers at the University of Osaka developed the Insect Synergy Circuit (ISC), a bio-hybrid AI system that monitors the heartbeat, neural signals, and body motion of Madagascar hissing cockroaches to guide them as cy…
Data engineering involves designing systems for collecting, storing, transforming, and managing data to support analytics, machine learning, and business decisions. The field relies on two primary ingestion methods: batc…
Wealth management firms are adopting data-driven personalization at scale, moving beyond basic digital tools toward operating models shaped by data science, artificial intelligence, automation, and portfolio engineering.…
Researchers at the Karlsruhe Institute of Technology (KIT) in Germany have demonstrated that standard WiFi networks can identify individuals with 99.5% accuracy by analyzing unencrypted beamforming feedback data using ma…
Researchers at the University of California Davis have developed a spectrometer-on-a-chip the size of a grain of sand that uses artificial intelligence and 16 specialized silicon sensors to analyze light and chemicals wi…
Three mathematicians have solved Talagrand's convexity conjecture, a decades-old problem in mathematics that its creator, Abel Prize winner Michel Talagrand, believed was unsolvable. Dongming Hua and Antoine Song from th…
The Google Tensor ML SDK has moved from an Experimental Access Program to Beta, now integrating with LiteRT to provide a unified API for deploying machine learning models on the Tensor Processing Unit (TPU) of Pixel 10 d…
Convergent infrastructure requirements for the foundation model lifecycle—including tightly coupled accelerator compute, high-bandwidth networking, and distributed storage—and highlights the growing reliance on open-sour…
Robust.AI selected Aptiv PLC's intelligent perception systems, including the Aptiv PULSE sensor, for its Gen 3 Carter collaborative mobile robot. The sensor fuses radar and vision using machine learning to improve reliab…
Researchers have developed a two-stage geometric registration method that aligns CAD models to CT scans of cylindrical objects by detecting elliptical cross-sections and estimating the 3D rotation axis. The approach achi…
Philosopher Daniel Fonseca argues that current large language models (LLMs) are fundamentally limited because they rely solely on statistical calculations, confusing quantity with quality. He proposes a hybrid model comb…
A new Likelihood Matching approach refines diffusion model training by aligning data distribution likelihoods, promising efficiency and accuracy in model generation. The method uses a quasi-likelihood to approximate reve…