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The field-deployed device systems Antmicro helps its customers build increasingly often use neural networks for tasks such as understanding voice commands, detecting, tracking and telling apart objects in video, or recognizing...
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Antmicro has been working with a large number of customers implementing AI software on embedded systems, helping utilize all the advantages of an open source-based approach. To achieve this we created a complete methodology...
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As part of our open source-centric strategy, Antmicro has been developing open source hardware which serves as a base for rapidly developing new, complex solutions - and our customers often reach out to us to lend them our...
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AI algorithms often require significant processing power typically associated with data centers. However, privacy concerns, latency and security considerations, together with increased compute capabilities of edge devices,...
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Kenning is Antmicro’s library aiming to simplify the workflow with machine learning applications on edge devices. It is used for testing and deploying ML pipelines on a variety of embedded platforms regardless of the underlying...
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The demand for deploying machine learning models, especially state-of-the-art deep neural networks on edge devices is rapidly growing. Edge AI allows to run inference locally, without the need for a connection to the cloud...
