Quantum computers, systems that process information leveraging quantum mechanical effects, will require faster and energy-efficient memory components, which will allow them to perform well on complex ...

A novel stacked memristor architecture performs Euclidean distance calculations directly within memory, enabling energy-efficient self-organizing maps without external arithmetic circuits. Memristors, ...

Ripple effect: DRAM prices have surged in recent months, and that spike is set to ripple far beyond memory modules themselves. As the shortage deepens and stretches into 2026, supply chain insiders ...

Abstract: Computing-In-Memory (CIM) is widely applied in neural networks due to its unique capability to perform multiply-and-accumulate operations within a circuit array. This process directly ...

Counterpoint warns that DDR5 RDIMM costs may surge 100% amid manufacturers’ pivot to AI chips and Nvidia’s memory-intensive AI server platforms, leaving enterprises with limited procurement leverage.

Just faced a weird memory leak in my code that uses both numpy and pytorch on cpu (to exploit some scipy functionalities first, before using pytorch ones). Here is a minimal example that reproduces ...

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Large language models (LLMs) like GPT and PaLM are transforming how we work and interact, powering everything from programming assistants to universal chatbots. But here’s the catch: running these ...

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 ...