Vector Post-Training Quantization (VPTQ) is a novel Post-Training Quantization method that leverages Vector Quantization to high accuracy on LLMs at an extremely low bit-width (<2-bit). VPTQ can ...
Francisco Javier Arceo explored Feast, the open-source feature store designed to address common data challenges in the AI/ML ...
To support professionals in overcoming this gap, we have selected five university-backed AI programs that emphasise ...
A Discrete Function (DF) Method for Highly Efficient Magnetization Vector Inversion of Magnetic Data
Abstract: The three-direction magnetization intensities of a source can be obtained by the magnetization vector inversion (MVI) of magnetic data, and therefore, MVI can be well applied to a magnetic ...
Koheesio is a versatile framework that supports multiple implementations and works seamlessly with various data processing libraries or frameworks. This ensures that Koheesio can handle any data ...
Amazon.com said it will invest $50 billion to expand artificial intelligence and high-performance computing capabilities for its cloud business’ U.S. government customers. The investment will add ...
Abstract: This paper introduces DSrepair, a knowledge-enhanced program repair approach designed to repair the buggy code generated by LLMs in the data science domain. DSrepair uses knowledge graph ...
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