GenAI isn’t magic — it’s transformers using attention to understand context at scale. Knowing how they work will help CIOs ...

VL-JEPA predicts meaning in embeddings, not words, combining visual inputs with eight Llama 3.2 layers to give faster answers ...

A research team has delivered an overview of how computational tools are reshaping the design of nonnatural metabolic pathways—engineered biochemical routes that do not exist in nature but enable ...

We have curated the best innovations of CES 2026, offering a look at standout products that push boundaries, rethink familiar ...

The production of too many useful things results in too many useless people.” That was Karl Marx, but it could as easily have ...

Slomp Filho, M. (2026) Copyright in Generative Artificial Intelligence. Beijing Law Review, 17, 1-10. doi: ...

Calculations show that injecting randomness into a quantum neural network could help it determine properties of quantum ...

This valuable study links psychological theories of chunking with a physiological implementation based on short-term synaptic plasticity and synaptic augmentation. The theoretical derivation for ...

Neuroscientists have been trying to understand how the brain processes visual information for over a century. The development ...

Early-2026 explainer reframes transformer attention: tokenized text becomes Q/K/V self-attention maps, not linear prediction.

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US researchers solve partial differential equations with neuromorphic hardware, taking us closer to world's first ...