Neural Networks news and analysis on Web Pulse: 1259 curated articles tracking the latest Neural Networks developments, tools, and research, updated continuously from vetted sources.
A developer manually computed gradients for a two-layer neural network with ReLU activation and squared-error loss, deriving ∂L/∂w1=30, ∂L/∂b1=30, ∂L/∂w2=20, and ∂L/∂b2=10, then verified that PyTorch's autograd produces …
A developer released Ditdah, a terminal-based Morse code decoding app built around a neural network, designed for amateur radio operators to practice conversational Morse at slow speeds. The app includes a logbook and QR…
Matt Mazur's tutorial 'A Step by Step Backpropagation Example' provides a concrete numerical example of the backpropagation algorithm for training a neural network, using a network with two inputs, two hidden neurons, tw…
A study published in Science found that inducing a hibernation-like state in mice caused the loss of more than half of their synapses, yet the mice retained their memories. Kazumasa Tanaka, a neuroscientist at the Okinaw…
An engineer reports that AI is transforming the field of mathematics, with machine learning models now capable of discovering new theorems and proofs. The project demonstrates how neural networks can assist mathematician…
A developer argues that genuine intelligence will never emerge from neural networks, regardless of scale, because they are fundamentally the wrong kind of system. The post contends that neural networks lack the capacity …
A new open-source macOS app, DesktopFly, simulates a 3D fruit fly on the desktop using a live spiking neural network based on the FlyWire connectome (v783), with 23,210 neuron soma positions and a 668-neuron circuit with…
Researchers from the National Institute for Basic Biology in Japan found that an artificial neural network trained on first-person videos of natural landscapes also perceives the Benham's Top optical illusion, producing …
Large language models (LLMs) consume roughly 20 watts of electricity per query, comparable to a phone charger, whereas the human brain operates on about 20 watts total, a figure refined over 600 million years of evolutio…
A new theory published in The Journal of Neuroscience by three scientists at MIT's Picower Institute for Learning and Memory proposes that cognition and consciousness arise from analog computations performed by traveling…
A new arXiv paper (2608.19584v1) studies loss landscapes for complex-parameterized neural networks, introducing a Kähler information metric and natural gradient descent that remains in the holomorphic tangent bundle. The…
A new arXiv preprint (2608.19632v1) finds that combining periodic (SIREN) activations with causal weighting in physics-informed neural networks (PINNs) reconstructs velocity and pressure fields for the DFG/Schafer-Turek …
Researchers propose 4MAS (4 Module Awake/Sleep), a novel macroarchitecture that models asymmetric brain hemispheres with separate long- and short-term memory mechanisms and a sleep phase between tasks to improve continua…
Researchers from an unnamed institution report that a contrastive decoder can extract open-vocabulary word-level information from non-invasive EEG during silent reading, achieving reliable above-chance word-grouped top-1…
Geneva-based Ability Neurotech has begun an intraoperative study in Germany, recording neural signals from patients undergoing brain tumor surgery in 20- to 30-minute sessions, and plans a chronic clinical trial in the N…
A new theory published in The Journal of Neuroscience proposes that cognition and consciousness arise from bidirectional interactions between neuronal spiking and rhythmic electric field activity, or brain waves, which e…
ONNX.css, a new open-source tool, compiles ONNX neural network models into CSS stylesheets, enabling browsers to run inference via the style engine. It demonstrates three models: a LeNet-style CNN for MNIST digit classif…
Researchers at the Center for Computational Neuroscience, Flatiron Institute, and New York University developed a computational framework integrating spectral regularization with bidirectional predictivity analyses, demo…
Researchers introduced AFANet, a lightweight graph neural network framework that matches or outperforms large language model-based baselines in agent failure attribution for multi-agent systems, with significantly fewer …
A new paper on arXiv (2007.13664) proves a universality result for neural network training: if any algorithm can find good weights for a classification task, then an extension of the network can reproduce those weights a…