The biggest memory burden for LLMs is the key-value cache, which stores conversational context as users interact with AI ...

Google unveils TurboQuant, PolarQuant and more to cut LLM/vector search memory use, pressuring MU, WDC, STX & SNDK.

Two parallel experiments in protein self-assembly produced strikingly different results, demonstrating that protein designers ...

A senior Meta researcher, Matt Motyl, said the company's competitor to TikTok, Instagram Reels, was launched in 2020 without ...

Cryptography secures communication in banking, messaging, and blockchain. Good algorithms (AES, RSA, ECC, SHA-2/3, ChaCha20) are secure, efficient, and widely trusted. Bad algorithms (DES, MD5, SHA-1, ...

ABSTRACT: The study adapts several machine-learning and deep-learning architectures to recognize 63 traditional instruments in weakly labelled, polyphonic audio synthesized from the proprietary Sound ...

Currently, the demo/ directory has limited examples demonstrating the use of the algorithms. Adding more Python examples will help new users understand how to work with the different algorithms ...

Algorithms, examples and tests for denoising, deblurring, zooming, dequantization and compressive imaging with total variation (TV) and second-order total generalized variation (TGV) regularization.

Abstract: In order to solve the problem of low optimization efficiency of the classical genetic algorithm, a parallel genetic algorithm optimization method is proposed to realize the CPU calling the ...

Professorship of Multiscale Modeling of Fluid Materials, Department of Engineering Physics and Computation, TUM School of Engineering and Design, Technical University of Munich, 80333 Munich, Germany ...