Neural Networks news and analysis on Web Pulse: 742 curated articles tracking the latest Neural Networks developments, tools, and research, updated continuously from vetted sources.
An independent research project analyzed the internal dynamics of small and medium-sized language models, revealing that functional properties become linearly decodable in hidden representations and that models cluster i…
An independent researcher analyzed hidden-state dynamics across seven open-weight LLMs and found recurring functional patterns encoded in representation geometry rather than individual neurons, with functional proxy stat…
Sean Xuefeng Du will present a new hallucination-detection method, Answer-agreement Representation Shaping (ARS), at ICML 2026 in Seoul on July 9. The work, developed at Nanyang Technological University, aims to detect w…
Power-law distributions in neural network weight matrices may explain the inductive bias toward sparse representations, according to research presented under the Iliad Fellowship. The generalized central limit theorem sh…
Tyler Suard released SYNAPSE, a browser game that teaches the math behind neural networks through 12 levels of tuning weights and biases. The game starts with single neurons and progresses to deep multi-layer networks, r…
A developer created Foveon, a Mac app that uses a modified U-Net deep learning model to transform photos from any Bayer-array camera into the distinctive look of a Sigma DP2 Merrill Foveon X3 sensor, known for its stacke…
An international consortium of researchers pooled brain imaging data from 273 adults across 11 independent datasets and found that psychedelics like psilocybin and LSD consistently increase functional connectivity betwee…
Researchers reverse-engineered the Apple Neural Engine (ANE), documenting its architecture, programming interface, and performance across A11-A18 and M1-M5 chips. The study reveals a direct user-space route to the ANE, t…
A developer built an AI agent using active inference that becomes curious on its own by minimizing surprise rather than chasing rewards. On a foraging task, the agent achieved 100% success by checking a hint before actin…
A developer created micrograd.ipynb, a tutorial that provides a spelled-out introduction to neural networks and backpropagation. The notebook walks through building a simple autograd engine from scratch, demonstrating th…
Shrijith Venkatramana, building git-lrc, explains that sequence transduction—transforming one sequence into another—was the original problem that led to modern large language models. Early neural networks like RNNs and L…
Chakradhar, a third-year BTech student, publicly documents his struggle to learn backpropagation as part of his journey to become an AI/ML engineer. He admits that the concept has 'broken his brain' and aims to share the…
Scientists at Mount Sinai discovered that deep brain stimulation for depression physically reshapes white matter in the brain, altering communication across neural networks. The study in Nature Neuroscience shows that lo…
Researchers introduced Tapered Language Models (TLMs), an architectural principle that allocates more parameter capacity to earlier layers and less to later layers under a fixed budget. Across four architectures and thre…
A developer implemented GPTQ quantization from scratch on a nanoGPT model, achieving only 1.1% perplexity degradation across 61 quantized layers. The implementation uses second-order optimization to redistribute quantiza…
Professor Igor Rudan of Edinburgh University proposed a radical new theory that consciousness evolved to simulate alternative futures, making it essential for human success. The theory suggests AI cannot become conscious…
Connectionist Temporal Classification (CTC) is an algorithm for training deep neural networks on sequence problems like speech and handwriting recognition where input-output alignment is unknown. CTC assigns probabilitie…
Researchers introduce forward self-models, small networks trained to predict a neural network's later-layer activations from earlier-layer activations, achieving up to 97% cosine similarity and 94% KL divergence recovery…
A developer building LSTMs with PyTorch and Lightning AI implemented the training_step function and ran initial predictions without training. The model predicted Company A's stock price reasonably close to the observed v…
A developer deployed a Cat vs Dog image classification web application on Vercel. The app uses a custom PyTorch CNN for predictions and displays confidence scores, evaluation metrics, and a confusion matrix. The tech sta…