Abstract: Guessing random additive noise decoding (GRAND) is a recently proposed universal maximum likelihood (ML) decoder for short-length and high-rate linear block codes. Soft-GRAND (SGRAND) is a ...
From $50 Raspberry Pis to $4,000 workstations, we cover the best hardware for running AI locally, from simple experiments to ...
Programming languages are evolving to bring the software closer to hardware. As hardware architectures become more parallel (with the advent of multicore processors and FPGAs, for example), sequential ...
Quilter's AI designed a working 843-component Linux computer in 38 hours—a task that typically takes engineers 11 weeks. Here's how they did it.
Neuromorphic computing holds the promise of sustainable AI by combining brain-inspired models with event-driven, massively parallel hardware. However, a central question remains: when and how do ...
A technical paper titled “Scalable Automatic Differentiation of Multiple Parallel Paradigms through Compiler Augmentation” was published by researchers at MIT (CSAIL), Argonne National Lab, and TU ...
Abstract: With the rapid deployment of Internet of things (IoTs), the production of data has been increasing exponentially. Due to this rapid data growth, the integration of deep learning model onto ...
Visual computing tasks such as 3D graphics and image processing are increasingly important to the capabilities and overall user experience delivered by computer systems ranging from high-end ...
Researchers from Rice University and startup xMAD.ai have detailed Dynamic-Length Float (DFloat11), a technique achieving approximately 30% lossless compression for Large Language Model weights stored ...
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