X admits its broken algorithm made the site feel like a ‘battleground’

X’s head of product, Nikita Bier, admitted in a post on Monday that X’s algorithm was “missing” data about surfacing posts ...

X is teaching its AI algorithm something social networks once understood

X is boosting posts among mutual followers after finding that relationship data was missing from its algorithm, exposing the gap between predicting engagement and creating conversations people ...
GitHub

FLUX: A Deep Learning Framework in C++ Built from First Principles

FLUX is an educational deep learning framework that reimplements the core functionality of PyTorch and TensorFlow from scratch, using only C++ and the Standard Template Library. No external ...
PNAS

Training neural networks using physical equations of motion

In this issue of PNAS, Dillavou et al. demonstrate an analog electronic system that relies exclusively on physical dynamics to optimally fit a nonlinear curve to a set of data points; a miniaturized ...
Frontiers

How can artificial neural networks approximate the brain?

The article reviews the history development of artificial neural networks (ANNs), then compares the differences between ANNs and brain networks in their constituent unit, network architecture, and ...
Frontiers

A Sparsity-Driven Backpropagation-Less Learning Framework Using Populations of Spiking Growth Transform Neurons

Growth-transform (GT) neurons and their population models allow for independent control over the spiking statistics and the transient population dynamics while optimizing a physically plausible ...
IEEE

Design of An Analog Circuit-Based Artificial Neural Network

Abstract: In this paper, a feed-forward artificial neural network with a single hidden layer has been realized using analog circuit blocks designed in 90 nm UMC technology. The network is capable of ...
IEEE

Learning in Memristive Neural Network Architectures Using Analog Backpropagation Circuits

Abstract: The on-chip implementation of learning algorithms would speed up the training of neural networks in crossbar arrays. The circuit level design and implementation of a back-propagation ...