Revolutionary technology achieves order-of-magnitude performance gains on standard CPUs, challenging fundamental assumptions about AI infrastructure requirements ...

Google LLC introduced two new custom silicon chips for artificial intelligence today at Google Cloud Next 2026, unveiling two ...

A neural network is a machine learning model originally inspired by how the human brain works (Courtesy: Shutterstock/Jackie Niam) Precision measurements of theoretical parameters are a core element ...

BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...

Anker's THUS chips embeds a processors on memory chips to reduce the energy consumption. Apple has done something simililar ...

NPU-equipped MCUs open the door to optimized edge AI in systems ranging from wearable health monitors to physical AI in ...

How a controversial tech from the 2000s could transform AI to make it cheaper, faster and almost indestructible.

We study deep neural networks and their use in semiparametric inference. We establish novel rates of convergence for deep feedforward neural nets. Our new rates are sufficiently fast (in some cases ...

A new technical paper titled “MultiVic: A Time-Predictable RISC-V Multi-Core Processor Optimized for Neural Network Inference” was published by researchers at FZI Research Center for Information ...

Gene regulatory networks (GRNs) depict the regulatory mechanisms of genes within cellular systems as a network, offering vital insights for understanding cell processes and molecular interactions that ...