Researchers generated images from noise, using orders of magnitude less energy than current generative AI models require.

SHANNON, CLARE, IRELAND, February 5, 2026 /EINPresswire.com/ -- A new publication from Opto-Electronic Technology; DOI ...

Researchers at the University of California, Santa Cruz have trained lab-grown brain organoids to solve a goal-directed task, ...

GlassAI Enables Real-Time RAW Video Processing on Snapdragon® 8 Elite (Gen 5) Platforms The Snapdragon 8 Elite (Gen 5) ...

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20^100 possible variants-more combinations than atoms in the observable universe.

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20100 ...

Imagine balancing a ruler vertically in the palm of your hand: you have to constantly pay attention to the angle of the ruler ...

AI became powerful because of interacting mechanisms: neural networks, backpropagation and reinforcement learning, attention, training on databases, and special computer chips.

Abstract: Spiking neural networks (SNNs) exhibit significant advantages in terms of information encoding, computational capabilities, and power usage. We regard initializing weight distribution as a ...

According to God of Prompt on Twitter, DeepMind researchers have identified a phenomenon called 'Grokking' where neural networks may train for thousands of epochs with little to no improvement, then ...

Neural networks first treat sentences like puzzles solved by word order, but once they read enough, a tipping point sends them diving into word meaning instead—an abrupt “phase transition” reminiscent ...