The Economist

AI models are being prepared for the physical world

They call it a “world model”, an essential tool to help AI systems make sense of the complex, unpredictable physical spaces ...
The Economist

To navigate physical spaces, AIs need world models

They call it a “world model”, an essential tool to help AI systems make sense of the complex, unpredictable physical spaces into which many will eventually be put to work. The company argues that a ...

Bringing quantum ideas to the messy world of disordered proteins

Imagine trying to design a key for a lock that is constantly changing its shape. That is the exact challenge we face in ...
IEEE

Physics-Informed Neural Networks for 3D Seismic Fault Segmentation with Topological and Geological Priors

Abstract: Seismic fault interpretation is a critical task for subsurface modeling and resource exploration. Although data-driven deep learning methods have shown considerable potential in automating ...
IEEE

Mapping Systolic Arrays onto 3D Circuit Structures: Accelerating Convolutional Neural Network Inference

Abstract: In recent years, numerous designs have used systolic arrays to accelerate convolutional neural network (CNN) inference. In this work, we demonstrate that we can further speed up CNN ...
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 ...