Nvidia’s new technique cuts LLM reasoning costs by 8x without losing accuracy

Nvidia researchers developed dynamic memory sparsification (DMS), a technique that compresses the KV cache in large language models by up to 8x while maintaining reasoning accuracy — and it can be ...
IEEE

Bidirectional Transfer Learning Between Activity and User Identity Recognition via 2D CNN-LSTM Model for Wearables

Abstract: We implement transfer learning (TL) to attain efficiency in training and feature extraction by freezing the connection weights of shallow layers of deep learning (DL) models, already trained ...

z.ai's open source GLM-5 achieves record low hallucination rate and leverages new RL 'slime' technique

The latest in z.ai's ongoing and continually impressive GLM series, it retains an open source MIT License — perfect for enterprise deployment – and, in one of several notable achievements, achieves a ...
Devdiscourse

Hybrid AI can reduce failures and energy use in manufacturing robots

The research, titled AI-Driven Hybrid Deep Learning and Swarm Intelligence for Predictive Maintenance of Smart Manufacturing Robots in Industry 4.0 and published in Electronics, introduces an AI ...
FinanceFeeds

Crypto Machine Learning Algorithms Explained for Beginners

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
IEEE

A Multi-Scale Deep Learning Framework Combining MobileViT-ECA and LSTM for Accurate ECG Analysis

Abstract: Electrocardiogram (ECG) analysis is crucial for diagnosing cardiovascular diseases (CVD), especially atrial fibrillation (AF), a prevalent cardiac rhythm abnormality. However, the ...
Science Daily

The deep ocean is fixing carbon in ways no one expected

Researchers have uncovered surprising evidence that the deep ocean’s carbon-fixing engine works very differently than long assumed. While ammonia-oxidizing archaea were thought to dominate carbon ...