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Simply mentioning supply chain delays, especially in the last few years, tends to create instant stress and headaches. This is especially true for embedded engineers that rely on specific components for their products. However, as we’ll see in this blog post, the right technology company can sometimes turn a component delivery delay into an opportunity!
You like running your machine learning (ML) workloads with the Qualcomm Adreno OpenCL ML SDK on Adreno GPUs. But you also want to use the optimized kernel library for Adreno, with the kind of end-to-end solution that comes from Tensor Virtual Machine (TVM) compiler infrastructure. Can you get the best of all worlds?
Humans have always envisioned that someday robots could perform work we don’t want to do, or necessarily need to do in person (e.g., repetitive or dangerous tasks) because robots may be more efficient. Today, service robots fulfill many tasks, including cleaning, providing directions, transporting products, etc. While humans will certainly continue doing many of these things (e.g., greeting visitors), there are certain aspects of this role such as providing directions that don’t need to be done by humans.
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