We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write ...

At the core of every AI coding agent is a technology called a large language model (LLM), which is a type of neural network ...

The researchers behind the recent work, based in China, decided to implement something similar for an artificial skin that ...

Overview: Clear problem definitions prevent wasted effort and keep machine learning work focused.Clean, well-understood data ...

Overview: AI skills are among the most in-demand career competencies in 2026 across industries.Leading EdTech platforms focus on hands-on projects and real-worl ...

Artificial intelligence is changing the way portfolios are built and managed. For a long time, investors relied mainly on ...

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...

This important study combines optogenetic manipulations and wide-field imaging to show that the retrosplenial cortex controls behavioral responses to whisker deflection in a context-dependent manner.

A new computational model of the brain based closely on its biology and physiology has not only learned a simple visual ...

Step aside, LLMs. The next big step for AI is learning, reconstructing and simulating the dynamics of the real world.

With more realistic images than before, GPT Image 1.5 fares reasonably well against Google's Nano Banana Pro in my testing.

What is the neuropsychological basis for the brain's ever-changing contextualized goals? I explore this question from the perspective of the Affect Management Framework (AMF).