Michigan Engineering | University of Michigan Machine learning will teach the world’s fastest machines to work smarter, not harder.
The post Rewriting the rules for supercomputers appeared first on Engineering Research News.
Blog
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Errors found in a bedrock contract bidding model—and how to solve them. A Q&A with Photios Ioannou
A flaw has been uncovered in construction’s best known and most cited competitive bidding model.
The post Errors found in a bedrock contract bidding model—and how to solve them. A Q&A with Photios Ioannou appeared first on Michigan Engineering News.
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Taking machine-learning models in health care from concept to bedside
The authors provide an overview of common challenges to implementing ML in a health-care setting, and describe the necessity of breaking down the silos in ML.
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Creating more efficient data centers for AI
Tang’s project will redesign data center systems to support large-scale use of hardware accelerators to meet future computational demand.
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Talking with touch
Nadine Sarter is pioneering the use of tactile interfaces to build better conversations between machines and humans
The post Talking with touch appeared first on Michigan Engineering News.
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U-M researchers provide control software to ensure autonomous vehicles stay in their lane
The team was awarded a Best New Application Paper Award by the IEEE Robotics and Automation Society for their work developing reliable control systems for Lane Keeping and Adaptive Cruise Control.
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New browser strategy game has players tackle real-life bat catastrophe
As a fungal infection ravages bat populations, the new game hopes to promote public awareness of ongoing research to combat the issue.
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Year of growth, experiments for May Mobility
May Mobility intends to gradually acclimate the public to the experience of autonomous driving.
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Prof. Kamal Sarabandi welcomes Emperor and Empress of Japan at IGARSS 2019
Predicting future disasters is an important goal of those participating in the IEEE Geoscience and Remote Sensing Symposium
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DARPA Award for more responsive AI that combines human and machine
The goal of Lasecki’s proposal is to create methods for making AI systems more robust and flexible.
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