Is it worth building sophisticated autonomous driving systems if their power consumption reduces an electric vehicle's range? Maybe yes.
In conversation with author and SEMICON West/ES Design West keynoter Bob Pearson on the challenges facing tech on external and internal communication.
Bob Smith of the ESD Alliance describes how we can promote the ongoing evolution of the design ecosystem.
The basics of USB 3.2, how to implement it in an SoC, and how USB Type-C connectors and cables are used in USB 3.2 systems.
Exchange frameworks are emerging to make it easier for neural-network developers to swap between development environments.
Machine-learning strategies for embedded vision are evolving so quickly that designers need access to flexible, heterogenous processor architectures that can adapt as the algorithms evolve.
An introduction to how virtual emulation has fueled the application of co-modeling for complex design verification.
Many car manufacturers are exploring the possibilities of autonomous vehicles. But what will it take to build sufficient AI performance into them to enable true autonomy?
Artificial intelligence and machine learning require the performance and flexibility offered by embedded FPGA (eFPGA) technology.
High-performance vision-processing algorithms need optimized CNN engines to deliver the right performance within the power budget of embedded applications.
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