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Traditional genetic programming relies on blind crossover, often breaking useful code. New methods like GP-GOMEA learn structure, preserve building blocks, and enable scalable software evolution.

Hruy argues that today’s online/social media platforms are deliberately designed to engineer artificial stupidity, quietly cultivating a future population optimized for content consumption rather than analysis and thought.

Scientists just cracked a decades-old problem: SPMiner uses Graph Neural Networks to discover hidden recurring shapes inside massive networks faster and at unprecedented scale.

Evolution meets quantum: GA4QCO uses genetic algorithms to automatically design high-fidelity quantum circuits, slashing manual trial-and-error in the NISQ era.

Bias is not just visible hatred but hidden programming. Examining history, culture, and AI, this piece asks: whose scriptures are scripting our systems—and whose future is being coded?

After 66 years, Dijkstra falls. A July 2025 breakthrough shatters the sorting barrier, proving faster shortest paths in directed graphs are possible without sorting everything and rewriting algorithmic theory forever

Shatter the sorting barrier: New hybrid algorithm reimagines network navigation, slashing computation time for real-time routing in traffic, internet, and beyond. Efficiency redefined.

A new algorithm uses time-series data to reveal hidden group interactions in dynamic systems like the brain.

John Hopfield and Geoffrey Hinton, two pioneers of machine learning and artificial neural networks, have won the Nobel Prize in Physics.

NeuroSA, a quantum-inspired tool, mimics brain functions to find optimal solutions for logistics, drug discovery, and more.