This year’s boom in artificial intelligence (AI), specifically generative AI, has made people reimagine what AI is capable of. Where a single machine learning model used to be capable of more singular ...
Learn how Apple's on-device AI hardware and future MacBook chips will introduce powerful MacBook AI features, boosting ...
A cohort of 20 undergraduate and first-year graduate students in computer science, computer engineering, and electrical engineering from Northwestern University, University of Illinois Chicago (UIC), ...
The machine learning (ML) revolution has drastically changed computation, and old computation paradigms have been overhauled and supplemented with new approaches in the last few years. This talk ...
Imagine a future where quantum computers supercharge machine learning—training models in seconds, extracting insights from massive datasets and powering next-gen AI. That future might be closer than ...
Create new power and memory efficient hardware architectures to meet next-generation machine learning hardware demands. Moving machine learning to the edge has critical requirements on power and ...
More aggressive feature scaling and increasingly complex transistor structures are driving a steady increase in process complexity, increasing the risk that a specified pattern may not be ...
Materials with advanced customized properties drive innovation in a number of real-life applications across various fields, such as information technology, transportation, green energy and health ...
Moving machine learning to the edge has critical requirements on power and performance. Using off-the-shelf solutions is not practical. CPUs are too slow, GPUs/TPUs are expensive and consume too much ...
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