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Hacked Suno source code reviewed by 404 Media reveals the AI music company scraped YouTube Music, Deezer, Genius, Pond5, Jamendo, Freesound, IMSLP, MuseScore and podcast RSS feeds to build training libraries, with one fi…
Researchers have introduced Bayesian deep ensembles, a new method that combines interpretability with high performance in predictive modeling. The approach uses low-dimensional ensemble representations and closed-form Ba…
A malware developer has embedded text related to nuclear and biological weapons in malicious code to evade detection by AI-powered security tools. The technique exploits content filters that avoid analyzing sensitive top…
Researchers have developed novel methods to combat data corruption in offline reinforcement learning with human feedback (RLHF), integrating corruption-robust techniques to derive reliable policies from tainted datasets.…
Onnes, a digital twin for dilution refrigerators, uses AI and LLM agents to improve fault diagnosis in quantum computing hardware, achieving 100% recall and near-perfect classification accuracy with minimal training data…
Primate Labs released Geekbench 7 on July 23 for macOS, iOS, Android, Windows, and Linux, adding AI, media, gaming, and content-creation workloads. The benchmark uses a new 2,500-point Ryzen 7 7700 reference baseline and…
A developer successfully ran an autoregressive language model on a 1975 MOS 6502 8-bit processor inside a BBC Micro, using BitNet ternary quantization to fit 13KB of model weights and 9KB of inference code within 25KB of…
Fusion energy is edging closer to practical use with AI-driven advances and better plasma containment, but the pathway to commercialization remains fraught with high costs and economic challenges. Artificial intelligence…
ECHO, a novel framework for traceable context reconstruction in agentic reinforcement learning, achieves 43.4% held-out accuracy on BrowseComp-Plus, outperforming GRPO's 28.9% and SUPO's 36.1% with fewer turns and lower …
Conditional Inference Forests (CIF) rank 4th among 17 classification methods and 3rd among 18 regression methods across multiple datasets, offering unbiased feature ranking despite runtime costs that can increase 4-11 ti…
Researchers have developed a new framework for detecting backdoor attacks in large language models, addressing the challenge of discrete input spaces. The framework introduces Class Subspace Orthogonalization (CSO) to en…
A developer's open-source security scanner for MCP servers, MCPSense, was flagged as a trojan by Windows Defender within its first week of release, with only 1 out of 71 antivirus engines on VirusTotal—Microsoft's—detect…
Neural networks and logistic regression models are competing to improve stroke prediction, as strokes occur every 40 seconds in the U.S. and are a leading cause of death. Neural networks offer complex pattern recognition…
Researchers have advanced Neural Controlled Differential Equations (NCDEs) with Log-NCDEs and Linear NCDEs, reducing training time by up to three orders of magnitude while achieving state-of-the-art results on time serie…
Researchers developed STST-JEPA, a self-supervised transformer model that predicts brain age from EEG data with a mean absolute error of 3.06 years, outperforming previous methods. The model, pretrained on over 47,000 se…
Ophiuchus, a new tool-augmented framework, outperforms existing methods in medical AI diagnostics by integrating fine-grained visual evidence with multimodal reasoning. Its three-stage training approach enables precise t…
Researchers have developed WattCouncil, a data-generation framework that uses large language model-based agents to simulate household energy data, addressing privacy and cost barriers in smart grid research. The framewor…
ManifoldFlow, a new approach to neural network weight constraints, introduces flexible spectral control by allowing a bounded positive spectrum instead of fixed singular values, outperforming traditional Stiefel layers i…
A new benchmarking framework for Graph Explainable AI (G-XAI) evaluates Graph Neural Networks (GNNs) using tabular explainability metrics that separate graph topology and node features, identifying non-dominated explaine…
AI integration in security systems requires human oversight to ensure accountability and adaptability, as shared architectures create blind spots and systemic errors. A balanced division of labor between AI and humans is…