A new study suggests that the brain processes information with high efficiency by synchronizing the physical wiring of neural ...

The representation of individual memories in a recurrent neural network can be efficiently differentiated using chaotic recurrent dynamics.

(A) Schematic illustration of the DishBrain feedback loop, the simulated game environment, and electrode configurations. (B) A schematic illustration of the overall network construction framework. The ...

In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...

Liquid AI, an AI startup co-founded by robotics luminary Daniela Rus, has raised $250 million in a Series A led by AMD. Per Bloomberg, the round values Liquid AI at over $2 billion. Liquid AI aims to ...

Many conventional computer architectures are ill-equipped to meet the computational demands of machine learning-based models. In recent years, some engineers have thus been trying to design ...

Researchers have developed a hybrid CFD-neural network model for predicting TAIs in hydrogen-fueled turbines, improving ...

When engineers build AI language models like GPT-5 from training data, at least two major processing features emerge: memorization (reciting exact text they’ve seen before, like famous quotes or ...

Cutting corners: Researchers from the University of California, Santa Cruz, have devised a way to run a billion-parameter-scale large language model using just 13 watts of power – about as much as a ...