The internet, social media, and digital technologies have completely transformed the way we establish commercial, personal and professional relationships. At its core, this society relies on the ...

“In-memory computing is an attractive alternative for handling data-intensive tasks as it employs parallel processing without the need for data transfer. Nevertheless, it necessitates a high-density ...

Most of the energy an AI chip burns never goes toward actual computation. It goes toward moving data: shuttling model weights ...

A new technical paper titled “Embedding security into ferroelectric FET array via in situ memory operation” was published by researchers at Pennsylvania State University, University of Notre Dame, ...

(Nanowerk Spotlight) The miniaturization of electronic components has been a driving force in technological advancement, pushing the boundaries of computing power and efficiency. As silicon-based ...

The RamSan-6200 uses single-level cell (SLC) NAND flash memory, multiple levels of RAID and advanced flash management algorithms to provide greater reliability. The SSD array is managed through Texas ...

A magnetic skyrmion is smaller than a virus, tougher to kill than most magnetic signals, and, if a growing body of laboratory research pans out, could one day store data using a fraction of the energy ...

Machine learning (ML), a subset of artificial intelligence (AI), has become integral to our lives. It allows us to learn and reason from data using techniques such as deep neural network algorithms.

For decades, compute architectures have relied on dynamic random-access memory (DRAM) as their main memory, providing temporary storage from which processing units retrieve data and program code. The ...

The big picture: If successfully scaled to industrial production, these chips could extend Moore's Law into the atomic domain by enabling far greater component density without incurring unsustainable ...