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The increasing availability of small, machine learning-capable devices is adding fuel to the growth of IoT, enabling ML tasks to be distributed from the cloud closer to where the data is produced. However, the development of complex edge-to-cloud ML systems...
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While developing FPGA designs it is important to keep track of resource usage and runtime to make sure that your development process is productive and your FPGA hardware delivers the best possible results. This is where one of our more recent developments...
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Antmicro’s Open Jetson Nano / Xavier NX Baseboard has been the basis for a number of our customer projects, allowing various computer systems that we build to leverage the AI-capabilities of NVIDIA’s popular SoMs. While providing full product development...
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It is becoming evident that the next level of advancement in chip-building can be achieved through open, modular and collaborative methodologies resulting in unmatched flexibility, ease of development and robustness of the end product. This approach is...
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The already high numbers of IoT devices shipped worldwide are expected to reach staggering levels in the nearest future. Yet, for many years, there wasn’t a high quality, fully reliable and widely reported benchmark for embedded computers that would accurately...
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Machine learning is still predominantly done in the cloud, which in many use cases may result in unnecessary latency, excessive power consumption and dependency on the availability of a wireless connection. Thanks to the recent developments in the area...
