Recent advances in neuroscience, cognitive science, and artificial intelligence are converging on the need for representations that are at once distributed, ...
The development of deep learning has motivated the advancement of unconventional computing that leverages analog physical ...
An analog in-memory compute chip claims to solve the power/performance conundrum facing artificial intelligence (AI) inference applications by facilitating energy efficiency and cost reductions ...
Listen to the first notes of an old, beloved song. Can you name that tune? If you can, congratulations — it’s a triumph of your associative memory, in which one piece of information (the first few ...
Skyrocketing AI compute workloads and fixed power budgets are forcing chip and system architects to take a much harder look at compute in memory (CIM), which until recently was considered little more ...
Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now A new neural-network architecture developed ...
Compute-in-memory (CIM) is not necessarily an Artificial Intelligence (AI) solution; rather, it is a memory management solution. CIM could bring advantages to AI processing by speeding up the ...
Recent advances in artificial intelligence (AI) and machine learning (ML) have transformed our ability to decode complex ...
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Overparameterized neural networks: Feature learning precedes overfitting, research finds
Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...
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