Neural Nexus: AI Networks Begin Teaching Themselves New Skills
Neural Nexus is our shorthand for an emerging class of AI systems that can discover and refine new abilities on their own. Instead of waiting for hand-labeled datasets, the model explores a safe goal space in simulation, ranks outcomes against general metrics like stability, efficiency, and novelty, and then compresses the best behaviors into reusable modules.
Those modules transfer across tasks — from robot control to language workflows — while guardrails (logging, red-teaming, and ability caps) keep improvements measurable and safe. The result is faster iteration, better cross-domain reuse, and surprising energy savings when policies learn to avoid idle work.
Videos
Neural Network Explained in 3 minutes
A fast-paced, simple explanation of how neural networks process data, recognize patterns, and make predictions — ideal for beginners.
Simple Neural Network in 3 Minutes
This short tutorial walks through the basics of building a simple neural network and training it to recognize color contrasts.
Neural Networks Explained – A Practical Insight
A concise and engaging visual guide to how neural networks mimic biological neurons and apply their learning to real-world problems.