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 ...

In trading, discussions often center on strategies, indicators, or market predictions. Yet behind the numbers lies a quieter factor that often determines whether a system can endure: position sizing.

This is a feature request to add a new 8-bit quantization method called Product Quantization with Residuals (PQ-R) to the bitsandbytes library. What is PQ-R? PQ-R is a hybrid quantization algorithm ...

A new technical paper titled “Cross-Layer Design of Vector-Symbolic Computing: Bridging Cognition and Brain-Inspired Hardware Acceleration” was published by researchers at Purdue University and ...

SAN FRANCISCO--(BUSINESS WIRE)--Elastic (NYSE: ESTC), the Search AI Company, announced new performance and cost-efficiency breakthroughs with two significant enhancements to its vector search. Users ...

Google’s June 2025 Core Update just finished. What’s notable is that while some say it was a big update, it didn’t feel disruptive, indicating that the changes may have been more subtle than game ...

1 Energy, Materials and Methods Research Laboratory, National High Polytechnic School of Douala, Douala, Cameroon. 2 National Advanced School of Engineering, University of Yaounde I, Yaounde, Cameroon ...

Support Vector Machines (SVMs) are a powerful and versatile supervised machine learning algorithm primarily used for classification and regression tasks. They excel in high-dimensional spaces and are ...