Researchers baked 3x inference speedups directly into LLM weights — without speculative decoding

Researchers from the University of Maryland, Lawrence Livermore, Columbia and TogetherAI have developed a training technique that triples LLM inference speed without auxiliary models or infrastructure ...
IEEE

Toward Transparent Reinforcement Learning: An Explainable Deep Q-Learning Framework for Sequential Decision-Making

Reinforcement learning (RL) has demonstrated remarkable promise in sequential decision-making tasks; however, its explainability issues continue to hinder high-stakes domains that demand regulatory ...

Sophelio Launches Data Fusion Labeler (dFL) to Accelerate Sensor Data Preparation for Machine Learning

Sophelio Introduces the Data Fusion Labeler (dFL) for Multimodal Time-Series Data - The only labeling and harmonization ...
ClutchPoints

Patriots’ Milton Williams sacks Sam Darnold deep in Seahawks territory during Super Bowl LX

The sack occurred with approximately 7:26 remaining in the third quarter. At that point in the game, the Seahawks held a 12-0 lead. They are looking to orchestrate a drive that could potentially put ...
IEEE

Sequential Feature-Augmented Deep Multilabel Learning for Compound Fault Diagnosis of Rotating Machinery With Few Labeled and Imbalanced Data

Abstract: Accurate fault diagnosis of rotating machinery is essential for smooth and safe operations of mechanical systems, and various data-driven methods have been developed based on massive sensing ...