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Collect, Store, And Analyze Data For Autonomous Fleets And ADAS In Real-time at the edge | Premio
Manage episode 303810962 series 2990367
Content provided by Thomas Riley. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Thomas Riley or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
Developing and improving autonomous vehicle systems and driver assistance systems (ADAS) requires massive real-world data from the various high-resolution cameras and vehicle sensors to train AV (autonomous vehicle) and ADAS (advanced driver assistant systems) algorithms. Obtaining this data requires purpose-built computing solutions capable of storing and recording data in real-time with speed and accuracy. Premio offers AI Edge Inference computers that are engineered for autonomous vehicle fleets and ADAS data deployments. Our AI Edge inference computers leverage the latest technologies in compute, storage, and connectivity to accelerate machine learning and real-time inference in the harshest environmental settings on and off the road.
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Manage episode 303810962 series 2990367
Content provided by Thomas Riley. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Thomas Riley or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
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Android Backstage, a podcast by and for Android developers. Hosted by developers from the Android engineering team, this show covers topics of interest to Android programmers, with in-depth discussions and interviews with engineers on the Android team at Google. Subscribe to Android Developers YouTube → https://goo.gle/AndroidDevs
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