Title: GitHub - NetSys/turbo: Autonomous driving advances rely on ML models whose compute needs exceed edge devices. While the cloud offers scale, networks are treated as bottlenecks, not part of control. We present TURBO, a cloud-augmented framework that jointly optimizes control and bandwidth across car and cloud, guaranteeing safety and improving accuracy by up to 15.6 %pt.
Open Graph Title: GitHub - NetSys/turbo: Autonomous driving advances rely on ML models whose compute needs exceed edge devices. While the cloud offers scale, networks are treated as bottlenecks, not part of control. We present TURBO, a cloud-augmented framework that jointly optimizes control and bandwidth across car and cloud, guaranteeing safety and improving accuracy by up to 15.6 %pt.
X Title: GitHub - NetSys/turbo: Autonomous driving advances rely on ML models whose compute needs exceed edge devices. While the cloud offers scale, networks are treated as bottlenecks, not part of control. We present TURBO, a cloud-augmented framework that jointly optimizes control and bandwidth across car and cloud, guaranteeing safety and improving accuracy by up to 15.6 %pt.
Description: Autonomous driving advances rely on ML models whose compute needs exceed edge devices. While the cloud offers scale, networks are treated as bottlenecks, not part of control. We present TURBO, a cloud-augmented framework that jointly optimizes control and bandwidth across car and cloud, guaranteeing safety and improving accuracy by up to 15.6 %pt. - NetSys/turbo
Open Graph Description: Autonomous driving advances rely on ML models whose compute needs exceed edge devices. While the cloud offers scale, networks are treated as bottlenecks, not part of control. We present TURBO, a cl...
X Description: Autonomous driving advances rely on ML models whose compute needs exceed edge devices. While the cloud offers scale, networks are treated as bottlenecks, not part of control. We present TURBO, a cl...
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