Neural Networks news and analysis on Web Pulse: 1262 curated articles tracking the latest Neural Networks developments, tools, and research, updated continuously from vetted sources.
A new blog series proposes that consciousness, free will, and related phenomena arise from the brain's predictive learning algorithm building generative models of itself, called 'intuitive self-models.' The series explor…
Researchers completed the first full wiring diagram of a fruit fly brain with 139,255 neurons and 50 million connections, using machine learning. The achievement raises questions about the simulation hypothesis, but the …
A developer detailed the architectural differences between NVIDIA's Ampere and Hopper GPU architectures, focusing on tensor core and memory bandwidth improvements. The Hopper architecture introduces Tensor Core 2.0 with …
A developer using PyTorch and Lightning AI demonstrated automated neural network training with GPU acceleration. By setting the trainer's accelerator and devices to 'auto', Lightning automatically detects and utilizes av…
A developer built an animated neural network visualization that shows forward pass, loss, and backpropagation in real time. The project uses Framer Motion for smooth animations and includes a fixed-timing system to ensur…
Senior engineers can now learn the internal architecture of large language models in a new five-part series. The second installment explains why recurrent neural networks have been replaced by transformers, which use att…
A developer has built a hybrid LLM-GNN framework to enhance the efficiency of ADAPT-QAOA for quantum circuit optimization. The model, which combines large language models with graph neural networks, achieved approximatio…
A growing body of research shows that lifelong learning helps older adults maintain brain health, independence, and social connection. Studies indicate that actively engaging in new skills strengthens neural pathways and…
New studies suggest consciousness may exist in organisms without brains, challenging the long-held assumption that subjective experience requires a neuronal system. Philosopher Natalie Lawrence argues that brain-centrism…
An engineer building with AI daily reveals that even the creators of large language models at Anthropic, Google DeepMind, and OpenAI do not fully understand why their models work. The post explains that LLMs encode knowl…
An engineer trained a neural network on 3,658 real patient records from the Framingham Heart Study and fit it into 8.9 kB of pure C code using Hasaki, a command-line tool for embedded systems. The model predicts systolic…
Neural Cellular Automata (NCA) extend Conway's Game of Life by learning neural network weights to solve problems like MNIST digit classification, maze solving, and playing Pong. NCA use local receptive fields and recurre…
DeepGate's automated model design system, combining neural architecture search, a compiler, and real-hardware measurements, produces models for microcontrollers that run up to 45× faster and use up to 11× less RAM than r…
Dropout, a regularization technique that randomly removes neurons during neural network training, helps prevent overfitting by forcing the network to distribute learning across multiple pathways, leading to better genera…
Researchers at Spain's University of Zaragoza scanned the brains of 100 young adults and found that right-wing authoritarians have reduced grey matter in the dorsomedial prefrontal cortex, a region linked to empathy and …
A team from Tsinghua University, the Chinese Academy of Sciences, and the University of Tokyo developed an all-organic, flexible brain-computer interface chip that retained 94% signal efficiency after 18 months in animal…
A loss function measures how wrong a machine learning model's predictions are, providing a feedback signal for improvement. High loss indicates large errors, while low loss means the model is close to correct. Common los…
A developer implemented real-time LiDAR room detection on an Arduino UNO Q using Edge Impulse, achieving high-accuracy environment classification without SLAM or computer vision. The system uses a 2D dToF LiDAR to create…
Sungkyunkwan University researchers led by professors Jo Sae-byeok and Yang Woo-seok developed a semiconductor synapse that strengthens or weakens memory by changing light wavelength, using disorder in an AgBiS2 heterost…
Sungkyunkwan University researchers developed a technology that strengthens or weakens AI semiconductor memory by changing light color, using material disorder and defects to mimic brain memory homeostasis. The team expe…