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 ...
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 Introduces the Data Fusion Labeler (dFL) for Multimodal Time-Series Data - The only labeling and harmonization ...
Machine learning models are increasingly applied across scientific disciplines, yet their effectiveness often hinges on heuristic decisions such as data transformations, training strategies, and model ...
From Cape Town to Tehran to Lima to Phoenix, dozens of cities across the globe have recently experienced water shortages. In the next five years the world’s demand for fresh water could significantly ...
Abstract: This paper presents a study on Dynamic Sequential Distribution Network Reconfiguration (DSDNR), which considers the sequential control of individual switches in real-time distribution ...
Protein design is crucial for the treatment of human diseases, but traditional protein design methods have some limitations. Site-directed mutagenesis is highly dependent on the physiological ...
Two particular phases in your nightly routine seem to play outsize roles in cognitive health. By Mohana Ravindranath A good night’s sleep isn’t just about the number of hours you log. Getting quality ...
Typically (but not always) found in specialized cars and motorcycles, a sequential manual transmission, often shortened to just "sequential," is a type of manual gearbox which, like a traditional ...
The tool, called Deep Research, arrives days after OpenAI released another one, which shops for groceries and books restaurant reservations. By Cade Metz A week ago, OpenAI released a tool that can go ...
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