Purposefully sinking boreal trees could help lock away carbon for millennia or longer, but the audacious plan comes with ...
China's DeepSeek has just published a new AI training method to scale models more easily. Analysts told Business Insider the approach is a "striking breakthrough." The paper comes as DeepSeek is ...
Chinese AI company Deepseek has unveiled a new training method, Manifold-Constrained Hyper-Connections (mHC), which will make it possible to train large language models more efficiently and at lower ...
Abstract: Navigating multiscale virtual environments necessitates an interaction method to travel across different levels of scale (LoS). Prior research has studied various techniques that enable ...
Abstract: With the rapid development and application of container cloud computing-related technologies, more and more applications are being deployed to container cloud clusters. As an essential ...
Diffusion models are widely used in many AI applications, but research on efficient inference-time scalability*, particularly for reasoning and planning (known as System 2 abilities) has been lacking.
A recent review in Nature Reviews Clean Technology presents, for the first time, a pathway for scaling up decoupled water electrolysis (DWE) technologies to produce industrial-scale green hydrogen.
Language models have shown great capabilities across various tasks. However, complex reasoning remains challenging as it often requires additional computational resources and specialized techniques.
Inference-time scaling can enhance the reasoning capabilities of large language models (LLMs) on complex problems that benefit from step-by-step problem solving. Although lengthening generated ...
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