O n Tuesday, researchers at Stanford and Yale revealed something that AI companies would prefer to keep hidden. Four popular ...

Abstract: Dedicated neural-network inference-processors improve latency and power of the computing devices. They use custom memory hierarchies that take into account the flow of operators present in ...

Researchers built autonomous robots the size of salt grains—with onboard computers, sensors, and motors that think and swim ...

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

Traditional post-training quantization (PTQ) methods suffer from severe degradation at extremely low bit-widths (1-2 bits). Vector quantization (VQ), while better, still struggles with diffusion ...

MemoryVLA is a Cognition-Memory-Action framework for robotic manipulation inspired by human memory systems. It builds a hippocampal-like perceptual-cognitive memory to capture the temporal ...

Hochul calls for action after 'timeout' boxes found at NY schools Bowen Yang leaving 'Saturday Night Live' after 6 years in shock exit Property owner on leafy Claremont Avenue faces nearly $1M fine ...

Abstract: The context and the state of mind are important retrieval cues for long-term memory, which helps information to be retrieved quickly. However, most memristive circuits focus on the process ...