As AI agents start to move faster than software made for human users, both digital tooling and silicon architecture need to be redesigned to reduce latency and power bottlenecks, according to the chie ...

rolvsparse© achieves 20–177× speedups and 98–99.5% energy savings on real Hugging Face production models. Even fully dense workloads — 0% sparsity — reach 63× acceleration, beating vendor-optimized ...

A paper from Google could make local LLMs even easier to run.

Alisson Becker has hailed one of his Liverpool teammates as a ‘special player’ who ‘always make a difference to the team’ whenever he’s on the pitch.DOWNLOAD THE OFFICIAL EMPIRE OF THE KOP ...

With SRAM failing to scale in recent process nodes, the industry must assess its impact on all forms of computing. There are ...

Abstract: Network sparsity or pruning is an extensively studied method to optimize the computation efficiency of deep neural networks (DNNs) for CMOS-based accelerators, such as FPGAs and GPUs. Though ...

Custom CUDA kernels for accelerating 1.58-bit ternary LLM inference with 2:4 structured sparsity on consumer Ampere GPUs. Exploits both ternary arithmetic (no multiplies) and hardware sparse tensor ...

Abstract: Compute-in-Memory (CiM) has emerged as a promising solution to address the memory bottleneck of von Neumann architectures. While SRAM-based CiM has seen significant progress due to mature ...

There seems to have been a mistake, and Samsung’s Galaxy S26 base model and Ultra variant are shipping with a display capable of 8-bit color, instead of 10-bit. This was always supposed to happen, but ...

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