Science – Page 139

From Field to Report: AI Automates Rocky Terrain Assessments

10.11.2025 by qfx

The automated generation of geotechnical reports proceeds not as construction, but as a cultivated flow, a methodology designed to anticipate and accommodate inevitable systemic drift within the report itself.

A new system leverages artificial intelligence to rapidly generate geotechnical reports from site data and imagery.

Hear This: Neural Networks Sharpen Audio Fingerprinting

10.11.2025 by qfx

A robust audio fingerprinting system leverages contrastive learning, where both original and intentionally degraded audio signals are processed through a shared encoder and projected into an embedding space, ultimately optimizing for invariance to common distortions like noise and reverberation.

Pretrained music models dramatically improve the accuracy and resilience of systems that identify audio, even with modifications.

Beyond the Hype: Forecasting with Graphs and Foundation Models

10.11.2025 by qfx

Time Series Forecasting Models (TSFM) operate on a five-minute sampling interval, establishing a granular temporal resolution for predictive analysis.

New research reveals that while foundation models excel at short-term forecasting, success isn’t guaranteed and depends heavily on the data itself.

Searching for Answers: The Challenge of Financial Information Retrieval

10.11.2025 by qfx

A query generation pipeline leverages both single- and multi-document approaches—the latter employing topic-based merging, context deepening, and comparative analysis—to produce inquiries subsequently vetted for quality and demonstrable answerability.

New research reveals current systems struggle with complex questions requiring synthesis from multiple financial documents.

Spotting the Flaws in Fake Data: A New Approach to Medical Image Quality

10.11.2025 by qfx

The proposed method rigorously identifies distortions in data attributable to network effects, thereby enabling precise artifact detection.

Researchers develop a method to automatically identify and remove artificial distortions in synthetic medical images, boosting their usefulness for training AI.

Self-Driving Cars Can Solve Traffic – By Acting in Their Own Self-Interest

10.11.2025 by qfx

Within a simulated environment of shared control, a learning system navigates the inherent unpredictability of autonomy, demonstrating that even the most sophisticated policies are ultimately grown from, and constrained by, the complexities of the world they inhabit.

New research shows that autonomous vehicles, when trained with artificial intelligence, can improve traffic flow by prioritizing their own goals.

Mapping Market Movements

10.11.2025 by qfx

Local estimations of Gaussian curvature reveal intermittent, regime-like bursts across diverse shapes—from benchmark models to real-world data—suggesting emergent patterns arise not from overarching design, but from localized geometric rules.

New research explores how the geometry of complex spaces can reveal hidden patterns in financial data.

Beyond ImageNet: Training AI to Spot Industrial Defects

10.11.2025 by qfx

Pretrained anomaly representations consistently elevate performance across diverse anomaly detection methods and network architectures, demonstrably surpassing the efficacy of original features as indicated by consistently superior results.

A new pretraining strategy focuses on learning feature representations specifically designed for the challenges of industrial anomaly detection.

When Agents Learn to Trade: Modeling Markets with Diverse Behaviors

10.11.2025 by qfx

A multi-agent reinforcement learning approach models financial markets by assigning unique traits to each agent, then governing their behavior with a shared policy optimized—through optimal transport calibration against real market data—to satisfy individual preferences within a limit order book environment.

New research shows that simulating financial markets with agents who learn and have unique preferences can recreate realistic trading patterns.

Predicting Pasture: Deep Learning Forecasts Irish Grass Growth

10.11.2025 by qfx

Ryegrass, subjected to the predictable rhythms of the months, demonstrates a growth pattern destined to plateau, a temporary flourishing inevitably constrained by inherent limitations.

A new approach to forecasting perennial ryegrass growth leverages the power of deep learning for optimized grassland management.