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Can AI truly invent instead of imitate? A groundbreaking logic framework enables machines to blend concepts creatively, producing original ideas in music, mathematics, and beyond.

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.

Stanford’s new GNN-powered method cracks the NP-hard subgraph matching problem, enabling fast motif discovery in massive graphs from biology to social networks.

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.

Tree-Miner: A breakthrough sequential pattern mining algorithm using compact SP-Tree for ultra-efficient discovery of frequent patterns even at low support thresholds.

Why just ask AI for answers when it can evolve them? LEAPS blends LLMs and evolutionary algorithms to generate, mutate, and refine solutions like nature.

Evolution in code has always been clumsy and wasteful. Now, GP-GOMEA teaches programs to protect what works and evolve with purpose.

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.

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?