A recent report explores how new non-volatile memories will play in monetizing AI, leading to significant revenue growth for ...
UD’s Tingyi Gu receives NSF CAREER award to study materials that can create more reliable, less energy-intensive forms of computer memory To develop the types of high-speed, energy-efficient ...
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Could Graphene Memristors Tackle AI's Energy Use?
This review asks whether graphene-based nanosensors could enhance energy efficiency in AI by integrating memory and computation for advanced information processing.
The hunt is on for anything that can surmount AI’s perennial memory wall–even quick models are bogged down by the time and energy needed to carry data between processor and memory. Resistive RAM (RRAM ...
Memories, both volatile and non-volatile are a critical element in various computing and logic devices, since that is where the data lives that is being processed. The mass market for memory ...
The expanded MRAM family now includes two new series, the Dual Quad Serial Peripheral Interface (Dual QSPI) series and the Parallel series, offering a comprehensive range of high-speed, non-volatile ...
A long-running problem in the computer world is that DRAM is the fastest memory available but also volatile, so it can't hold onto its data when power is shut off. This makes it useless for data ...
A novel type of three-dimensional (3D) polar topological structure, termed the "polar chiral bobber," has been discovered in ...
Artificial Intelligence (AI) and Machine Learning (ML) applications are driving increased demand for high-performance, low-power memory solutions across consumer, medical, and industrial markets.
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