Machine learning news — deep learning, reinforcement learning, neural architecture search, diffusion models, and new ML frameworks and libraries.
Northeastern University professor Yongmin Liu is developing optical metasurfaces that use light instead of electricity to run AI models, aiming for extremely low power consumption and high speed. With a recent National S…
Kimi K3, an AI model from Moonshot AI, introduces Attention Residuals, replacing standard uniform residual connections in deep transformers with attention-weighted layer outputs, allowing the model to dynamically weight …
SandboxAQ launched AQPotency on August 19, a virtual-screening model that ranks potential drug compounds without requiring a solved 3D protein structure, priced at $1 per 1,000 molecule-target comparisons. The model is a…
Ornith AI released Ornith-1.5 on August 19, 2026, an open model family that generates its own training tasks, extending self-scaffolding into task generation. The models propose harder problems, build evaluation harnesse…
SAP's acquisition of tabular foundation model startup Prior Labs for over €1 billion ($1.16 billion) has spotlighted the emerging category of TFMs, which are designed to handle structured data like spreadsheets that larg…
Microsoft's GraphRAG system addresses the limitations of standard Retrieval-Augmented Generation (RAG) for global queries that require reasoning across entire document collections, using knowledge graphs and community de…
A study published in Nature, led by Devon Stoliker from Monash School of Psychological Sciences, found that individual brain patterns during psychedelic trips show hidden order rather than the chaos seen in group average…
Google's Pixel Watch 5, launching August 20, will include an Insulin Resistance Trends feature that uses wrist-based sensors to estimate insulin resistance, with validation accuracy of 75% using wearable data alone and 8…
Ornith-1.5, a new family of foundation models from the Ornith project, achieves state-of-the-art performance among open-source models of comparable size, with the flagship Ornith-1.5-397B scoring 86.1 on Terminal-Bench 2…
A vLLM RFC from the llm-d team warns that disaggregated inference deployments, where prefill and decode run on separate schedulers, can trigger recomputation-based preemption inside the decode instance, forcing it to red…
Developer 'davidb' released Scrollcase, an open-source tool that packages Python and machine-learning projects into self-contained, verifiable boxes, eliminating the need for Python installs, pip installs, or Docker. The…
Conversationaly, a privacy-first AI meeting assistant for macOS, Windows, and Linux, records meetings, transcribes them live, and generates summaries entirely on-device by default, with no account, cloud round-trip, or t…
DeepReinforce released Ornith-1.5, a family of open models in 397B, 35B, and 9B sizes, extending the self-scaffolding framework into a closed self-improvement loop where the system proposes tasks, generates scaffolds, an…
WhatsApp is testing Scam Alert, an optional on-device machine learning feature that warns users when messages from non-contacts match scam patterns, using confidential computing, differential privacy, and transparency me…
A developer demonstrates how to run fine-tuned large language models on Apple Silicon using MLX Swift bindings, bypassing CoreML's compilation latency. The approach uses lazy evaluation, direct loading of .safetensors we…
Liquid AI released Q4_0 checkpoints for its LFM2.5 language models trained with quantization-aware distillation (QAD), recovering 96.5% to 97.4% of the accuracy lost to quantization across four models. The QAD checkpoint…
Packt has published 'The Ultimate AI Guide for Linux Engineers' by Ezequiel Lanza and Eduardo Spotti, a 300-page, 12-chapter book aimed at seasoned Linux professionals such as sysadmins and DevOps engineers, covering AI/…
Sarvam AI's Saaras V3 speech recognition model achieved a word error rate of approximately 19.3% on the IndicVoices top-10 language benchmarks, outperforming OpenAI's GPT-4o Transcribe, ElevenLabs' Scribe v2, Google's Ge…
Data leakage in machine learning can cause models to achieve 98% accuracy during evaluation but fail in production, according to a technical explainer. The article warns that preprocessing steps like mean imputation and …
TESSRAL, a deeptech product, enables users to train their own image or voice AI models on personal hardware with small datasets, eliminating the need for massive GPU clusters or cloud compute. The product allows users to…