Tenstorrent QuietBox tested: A high-performance RISC-V AI workstation trapped in a software blackhole

The $12K machine promises AI performance can scale to 32 chip servers and beyond but an immature software stack makes ...
Medscape

Machine Learning Algorithm Predicts Gout Flares Using RNA

Researchers analyzed clinical data and RNA expression from the peripheral blood of 174 patients with gout and hyperuricemia that had been collected at week 48 of their participation in the STOP Gout ...
Hosted on MSN

Backpropagation from Scratch in Python – Step by Step Neural Network Tutorial

Learn how backpropagation works by building it from scratch in Python! This tutorial explains the math, logic, and coding behind training a neural network, helping you truly understand how deep ...
IEEE

Quantum Gated Recurrent Neural Networks

Abstract: The exploration of quantum advantages with Quantum Neural Networks (QNNs) is an exciting endeavor. Recurrent neural networks, the widely used framework in deep learning, suffer from the ...
insideHPC

D-Wave Introduces Quantum AI Developer Toolkit

PALO ALTO, Calif. – August 4, 2025 – D-Wave Quantum Inc. (NYSE: QBTS) announced it has released a collection of offerings to help developers explore quantum artificial intelligence and machine ...
GitHub

Learn PyTorch for Deep Learning

Welcome to the Zero to Mastery Learn PyTorch for Deep Learning course, the second best place to learn PyTorch on the internet (the first being the PyTorch documentation). 00 - PyTorch Fundamentals ...
Hosted on MSN

Network in Network Deep Neural Network Explained with PyTorch

Learn about the Network in Network architecture and its impact on improving performance in deep neural networks using PyTorch. Maddow Blog | Rubio’s latest moves raise fresh doubts about the future of ...
IEEE

Comparative analysis on Deep Convolution Neural Network models using Pytorch and OpenCV DNN frameworks for identifying optimum fruit detection solution on RISC-V architecture

Abstract: Making computer detect desired object have always been an area of interest for humans. Object detection can be implemented using following stages: feature extraction, object localization ...