Machine learning news — deep learning, reinforcement learning, neural architecture search, diffusion models, and new ML frameworks and libraries.
ANEForge, a new open-source Python package, compiles tensor graphs directly into programs for the Apple Neural Engine (ANE) and runs them without CoreML, enabling both inference and training on the chip Apple designed on…
FeyNoBg, a high-precision background removal model developed by Feyn Inc., achieves top-tier scores across eight benchmarks by expanding the third stage of its BiRefNet-based feature extractor from 18 to 24 blocks using …
Myriad Genetics and AWS reported in November 2025 that a generative-AI document pipeline lifted classification accuracy from 94% to 98% while cutting per-page classification costs 77%, from 3.1 cents to 0.7 cents per pag…
Vladimir Vapnik and Alexey Chervonenkis, two Soviet mathematicians, laid the mathematical foundation of machine learning with their 1964 paper introducing VC theory, which formalized generalization bounds, capacity contr…
A developer built rai-lint, a linter that enforces AI attribution footers in Git commits, and rai-commit-badge, a GitHub Action that reads those footers to generate a Shields.io badge showing the percentage of AI-written…
Myriad Genetics rebuilt its AI platform after costs ballooned, and now processes documents in 20 seconds instead of 10 minutes, accelerating repayment cycles. The Salt Lake City-based molecular diagnostic testing company…
Moonshot AI's Kimi team and kvcache-ai have open-sourced AgentENV (AENV), a distributed platform for running agent environments at scale that powers agentic reinforcement learning (RL) training for Kimi K3, Moonshot's 2.…
Lorraine, an open-source Flutter meeting recorder for macOS, captures system audio and microphone, transcribes meetings locally or via a Modal deployment running WhisperX, and recognizes speakers across sessions using vo…
Ramp engineers developed a Thompson-sampling-based router that dynamically selects the most cost-effective large language model for each query, reducing inference costs by up to 40% while maintaining response quality. Th…
An AI-designed radio-frequency chip that outperforms human-engineered designs has been tested, verified, and shipped, yet engineers cannot explain why its chaotic, QR-code-like layout works. Researchers used reinforcemen…
University of Southern California researchers have developed an algorithm called Vibrotactile Preference Learning (VPL) that efficiently learns an individual's preferred vibration patterns for producing a desired emotion…
PostSlate, a video editing startup, achieves up to 10x faster inference on edge devices by switching from ONNX Runtime CPU to ncnn with Vulkan GPU backend, with ArcFace R50 dropping from 30 ms to 3 ms and SCRFD face dete…
PLOS Computational Biology published ALFAssay on July 27, a feed-forward neural-network pipeline that estimates circulating tumor DNA fractions from cell-free DNA fragmentation profiles in breast cancer. Across 896 plasm…
A new study from researchers argues that language model harnesses, specifically Recursive Language Models (RLMs), can achieve compositional generalization by shaping each call to the underlying Transformer so that every …
A new analysis explains how mode-agile threats render static library radar and electronic warfare systems ineffective, and how AI/ML cognitive architectures using artificial neural networks, deep neural networks, fuzzy l…
Feyn released FeyNoBg, an automatic background removal model, and open-sourced NoBg, a Python library for training and running such models. The model achieves the best published score on four of eight benchmarks and come…
Atlas Discovery launched out of stealth with foundation models that predict individual patient drug responses in clinical trials, targeting the costly gap between preclinical results and human efficacy. Y Combinator gene…
Whatnot, a live-shopping platform, presented a blueprint for observability at scale at Snowflake Summit 2026, detailing how it uses automated AI analysts and platform monitoring to handle billions of daily data points. T…
A new approach to test datasets for generalised machine learning tasks proposes drawing the test set from a distribution as different as possible from the training and validation sets, while still being in-distribution f…
A developer demonstrated the utility of Royston-Parmar (RP) models for causal inference in survival analysis, particularly in scenarios with non-proportional hazards where Cox proportional hazards models fail. The code, …