Google researchers have revealed that memory and interconnect are the primary bottlenecks for LLM inference, not compute power, as memory bandwidth lags 4.7x behind.

The artificial intelligence buildout is quietly rewriting the semiconductor pecking order, shifting pricing power from headline-grabbing compute chips to the memory and storage that feed them. As ...

Content Addressable Memory (CAM) is an advanced memory architecture that performs parallel search operations by comparing input data against all stored entries simultaneously, rather than accessing ...

Ferroelectric quantum dots enable phototransistors that adapt to low light and store visual memory, supporting motion recognition and in-sensor learning in neuromorphic systems. (Nanowerk Spotlight) ...