‘The Karpathy Loop’: Former OpenAI researcher’s autonomous agents ran 700 experiments in 2 days—and gave a glimpse of where AI is heading

Karpathy's 'autoresearch' agent did not improve its own code, but it points towards systems that could as well as towards way ...
IEEE

A Recursive Discovery of Fractional Dynamics and Its Informed Neural Network Framework With Applications to Heterogeneous Transportation Carbon Emission Forecast

Abstract: The provincial transportation carbon emissions (TCEs) in China exhibit spatiotemporal heterogeneous characteristics and have become increasingly unpredictable in recent years. To this end, ...
GitHub

Neural Network from Scratch

Eric Gutiérrez, 6th February 2026. A Python implementation of a 1-hidden layer neural network built entirely from first principles. This project avoids deep learning libraries (like TensorFlow or ...
Hosted on MSN

Neural network Python from scratch with softmax

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...
Hosted on MSN

Python neural network for multiclass classification using softmax

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...
IEEE

Recursive Neural Network POS Tagger

This project explores the application of recursive neural networks (RNNs) in natural language processing, specifically for part-of-speech (POS) tagging. Drawing on foundational work by Socher et al.
The Verge

What happens when you feed AI nothing

Artist Terence Broad makes AI produce images without any training data at all. Artist Terence Broad makes AI produce images without any training data at all. But Broad didn’t train his AI on Rothko; ...
Phys.org

Self-learning neural network cracks iconic black holes

A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions of synthetic black hole data sets. Based on the network and data from the ...
Scientific Research Publishing

Leshno, M., Lin, V.Y., Pinkus, A. and Schocken, S. (1993) Multilayer Feedforward Networks with a Nonpolynomial Activation Function Can Approximate Any Function. Neural Networks ...

ABSTRACT: We explore the performance of various artificial neural network architectures, including a multilayer perceptron (MLP), Kolmogorov-Arnold network (KAN), LSTM-GRU hybrid recursive neural ...