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 framework. Based on a variety of practical edge AI use cases that we are working with on a daily basis, we have now expanded its functionality to include an environment that will help with development of final applications. Expanding the use case beyond just testing ...| antmicro.com
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, are making local AI data preprocessing increasingly common.| antmicro.com
Development of Machine Learning algorithms which enable new and exciting applications is progressing at a breakneck pace, and - given the long turnaround time of hardware development - the designers of dedicated hardware accelerators are struggling to keep up. FPGAs offer an interesting alternative to ASICs, enabling a much faster and more flexible environment for such HW-SW co-development - and with projects such as the FPGA interchange format, Antmicro has been turning the FPGA ecosystem to...| antmicro.com